From 824c7a0b53fa3dc7cc1363b8b9b8b9ed3c63e50d Mon Sep 17 00:00:00 2001
From: Baptiste Bauvin <baptiste.bauvin@lis-lab.fr>
Date: Wed, 29 Apr 2020 09:38:45 -0400
Subject: [PATCH] Reloaded ipynb
---
demo/tutorials/getting_started.ipynb | 10 +-
demo/tutorials/sample_types.ipynb | 4978 +----------------
.../sub_problems_configuration.ipynb | 46 +-
3 files changed, 28 insertions(+), 5006 deletions(-)
diff --git a/demo/tutorials/getting_started.ipynb b/demo/tutorials/getting_started.ipynb
index 3f264ac..74888ab 100644
--- a/demo/tutorials/getting_started.ipynb
+++ b/demo/tutorials/getting_started.ipynb
@@ -342,7 +342,7 @@
"shuffle: false\n",
"```\n",
"\n",
- "This report has been automatically generated on April 22, 2020 at 13:34:04"
+ "This report has been automatically generated on April 29, 2020 at 09:34:50"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
@@ -33603,20 +33603,20 @@
"<div>\n",
" \n",
" \n",
- " <div id=\"4d74e31a-6f08-4700-991d-4aa8b9d46ea1\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
+ " <div id=\"4552079b-48ed-48b0-a0a2-980d18470b53\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
" <script type=\"text/javascript\">\n",
" require([\"plotly\"], function(Plotly) {\n",
" window.PLOTLYENV=window.PLOTLYENV || {};\n",
" \n",
- " if (document.getElementById(\"4d74e31a-6f08-4700-991d-4aa8b9d46ea1\")) {\n",
+ " if (document.getElementById(\"4552079b-48ed-48b0-a0a2-980d18470b53\")) {\n",
" Plotly.newPlot(\n",
- " '4d74e31a-6f08-4700-991d-4aa8b9d46ea1',\n",
+ " '4552079b-48ed-48b0-a0a2-980d18470b53',\n",
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diff --git a/demo/tutorials/sample_types.ipynb b/demo/tutorials/sample_types.ipynb
index f17d8ff..350cb7a 100644
--- a/demo/tutorials/sample_types.ipynb
+++ b/demo/tutorials/sample_types.ipynb
@@ -116,19 +116,7 @@
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"name": "#%% \n"
}
},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Start:\t Initializing monoview classifiers arguments\n",
- "Done:\t Initializing monoview classifiers arguments\n",
- "Start:\t Initializing monoview classifiers arguments\n",
- "Done:\t Initializing monoview classifiers arguments\n",
- "Start:\t Executing all the needed benchmarks\n",
- "Start:\t Benchmark initialization\n",
- "Done:\t Benchmark initialization\n",
- "Start:\t monoview benchmark\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.014620825997553766[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef7558>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5245245245245245\n",
- "\t\t- Score on test : 0.5405405405405406\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 195 │ 71 │ 67 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 91 │ 147 │ 95 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 60 │ 75 │ 198 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= -8.986247539520264\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.593865779915303\n",
- "- Feature index : 2, feature importance : 0.37775762340238894\n",
- "- Feature index : 0, feature importance : 0.028376596682308103\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.02298176399199292[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.44344344344344344\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 140 │ 95 │ 98 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 89 │ 145 │ 99 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 72 │ 103 │ 158 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3622416671310541\n",
- "- Feature index : 2, feature importance : 0.3411227657434244\n",
- "- Feature index : 0, feature importance : 0.29663556712552147\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
- "0.0 | 1.0\n",
- "1.0 | 0.0\n",
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- "1.0 | 0.0\n",
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- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.042979129997547716[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef7558>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.973973973973974\n",
- "\t\t- Score on test : 0.44044044044044045\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 160 │ 93 │ 80 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 116 │ 137 │ 80 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 92 │ 98 │ 143 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.34810232453346884\n",
- "- Feature index : 0, feature importance : 0.3348437348480852\n",
- "- Feature index : 2, feature importance : 0.317053940618446\n",
- "\n",
- "Done:\t Saving results\n",
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- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
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- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
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- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.01366416399832815[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef7558>\n",
- "\t- Executed on 1 core(s) \n",
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- "\t\t- Score on train : 0.5625625625625625\n",
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- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 174 │ 85 │ 74 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 65 │ 207 │ 61 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 79 │ 104 │ 150 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= 0.11212348937988281\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.6120220280042745\n",
- "- Feature index : 0, feature importance : 0.38797797199572553\n",
- "\n"
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
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- "Info:\t Duration for training and predicting: 0.02157829000498168[s]\n",
- "Start:\t Getting results\n",
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- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
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- "\t- Labels used : label_1, label_2, label_3\n",
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- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 120 │ 97 │ 116 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 89 │ 130 │ 114 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 81 │ 127 │ 125 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3581427826162341\n",
- "- Feature index : 0, feature importance : 0.3320074059539233\n",
- "- Feature index : 2, feature importance : 0.3098498114298425\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
- "0.0 | 1.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
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- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.03333836898673326[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef7558>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.973973973973974\n",
- "\t\t- Score on test : 0.44344344344344344\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 163 │ 75 │ 95 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 94 │ 149 │ 90 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 92 │ 110 │ 131 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.35063866653989983\n",
- "- Feature index : 2, feature importance : 0.32761820411732384\n",
- "- Feature index : 0, feature importance : 0.3217431293427764\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.011298666999209672[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef7558>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5445445445445446\n",
- "\t\t- Score on test : 0.5455455455455456\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 199 │ 64 │ 70 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 64 │ 194 │ 75 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 77 │ 104 │ 152 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= -1.1316807270050049\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.5603538640891512\n",
- "- Feature index : 0, feature importance : 0.4396461359108487\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.016297076013870537[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.4134134134134134\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 152 │ 102 │ 79 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 91 │ 135 │ 107 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 99 │ 108 │ 126 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3621281243886289\n",
- "- Feature index : 0, feature importance : 0.3497804668765774\n",
- "- Feature index : 2, feature importance : 0.2880914087347936\n",
- "\n",
- "\n",
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- "text": [
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.04144220901071094[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef7558>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.9719719719719719\n",
- "\t\t- Score on test : 0.4494494494494494\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 171 │ 91 │ 71 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 90 │ 159 │ 84 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 90 │ 124 │ 119 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.36396500099010287\n",
- "- Feature index : 0, feature importance : 0.3277636019905735\n",
- "- Feature index : 2, feature importance : 0.30827139701932366\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.011509386007674038[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef7558>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5475475475475475\n",
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- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 196 │ 64 │ 73 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 64 │ 194 │ 75 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 96 │ 105 │ 132 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= 7.099114418029785\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.5782256722519781\n",
- "- Feature index : 2, feature importance : 0.38786245664154767\n",
- "- Feature index : 0, feature importance : 0.033911871106474235\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.017198485002154484[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.3863863863863864\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 136 │ 83 │ 114 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 91 │ 145 │ 97 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 114 │ 114 │ 105 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3584041021628971\n",
- "- Feature index : 2, feature importance : 0.3334659557746437\n",
- "- Feature index : 0, feature importance : 0.30812994206245925\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.03872804998536594[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef7558>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.968968968968969\n",
- "\t\t- Score on test : 0.44244244244244246\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 176 │ 75 │ 82 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 97 │ 163 │ 73 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 131 │ 99 │ 103 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.34828717578196294\n",
- "- Feature index : 2, feature importance : 0.33209362138174287\n",
- "- Feature index : 0, feature importance : 0.31961920283629414\n",
- "\n"
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- "Done:\t Saving results\n",
- "Done:\t monoview benchmark\n",
- "Start:\t multiview arguments initialization\n",
- "Done:\t multiview arguments initialization\n",
- "Start:\t multiview benchmark\n",
- "Done:\t multiview benchmark\n",
- "Start:\t Analyzing all results\n",
- "Start:\t Score graph generation for accuracy_score*\n",
- "Done:\t Score graph generation for accuracy_score*\n",
- "Start:\t Label analysis figure generation\n",
- "locator: <matplotlib.ticker.FixedLocator object at 0x7f28541aedd8>\n",
- "Using fixed locator on colorbar\n",
- "Setting pcolormesh\n",
- "Done:\t Label analysis figures generation\n",
- "Done:\t Analyzing all results\n",
- "Start:\t Benchmark initialization\n",
- "Done:\t Benchmark initialization\n",
- "Start:\t monoview benchmark\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.013571974996011704[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef0090>\n",
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- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5445445445445446\n",
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- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 189 │ 68 │ 76 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 90 │ 136 │ 107 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 67 │ 70 │ 196 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= -8.986247539520264\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.5472671261284495\n",
- "- Feature index : 2, feature importance : 0.3018988800753102\n",
- "- Feature index : 0, feature importance : 0.1508339937962403\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.017609995004022494[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
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- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
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- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 136 │ 105 │ 92 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 95 │ 124 │ 114 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 91 │ 86 │ 156 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.39032418528177976\n",
- "- Feature index : 2, feature importance : 0.32614691556549413\n",
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- "\n",
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
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- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.03328543298994191[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef0090>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.968968968968969\n",
- "\t\t- Score on test : 0.44344344344344344\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 174 │ 77 │ 82 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 101 │ 129 │ 103 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 97 │ 96 │ 140 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 2, feature importance : 0.3508015514043997\n",
- "- Feature index : 1, feature importance : 0.3411023669702324\n",
- "- Feature index : 0, feature importance : 0.30809608162536795\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.009463227004744112[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n"
- ]
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- "text": [
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
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- "\t- Labels used : label_1, label_2, label_3\n",
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- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 166 │ 81 │ 86 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 70 │ 202 │ 61 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 73 │ 106 │ 154 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= -8.185171604156494\n",
- "Feature importances : \n",
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- "- Feature index : 0, feature importance : 0.3209794197164746\n",
- "- Feature index : 2, feature importance : 0.09161950720202482\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
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- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.016291387000819668[s]\n",
- "Start:\t Getting results\n",
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- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
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- "Classifier configuration : \n",
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- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 146 │ 71 │ 116 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 102 │ 131 │ 100 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 94 │ 102 │ 137 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
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- "- Feature index : 0, feature importance : 0.3414719725150146\n",
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- "\n",
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- " Estimator error | Estimator weight\n",
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.03930041799321771[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef0090>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.9679679679679679\n",
- "\t\t- Score on test : 0.4624624624624625\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 166 │ 79 │ 88 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 94 │ 161 │ 78 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 102 │ 96 │ 135 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3785623571312163\n",
- "- Feature index : 0, feature importance : 0.33402875405488996\n",
- "- Feature index : 2, feature importance : 0.2874088888138938\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.01120196800911799[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef0090>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5575575575575575\n",
- "\t\t- Score on test : 0.5185185185185185\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 206 │ 63 │ 64 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 85 │ 182 │ 66 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 111 │ 92 │ 130 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= -1.0831778049468994\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.5456660892016889\n",
- "- Feature index : 0, feature importance : 0.4197391986254741\n",
- "- Feature index : 2, feature importance : 0.034594712172837064\n",
- "\n"
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.019016871985513717[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.3683683683683684\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 113 │ 98 │ 122 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 94 │ 136 │ 103 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 108 │ 106 │ 119 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.35732844280955095\n",
- "- Feature index : 0, feature importance : 0.3377112111592173\n",
- "- Feature index : 2, feature importance : 0.3049603460312318\n",
- "\n",
- "\n",
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.045145098003558815[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef0090>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.9669669669669669\n",
- "\t\t- Score on test : 0.4094094094094094\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 151 │ 95 │ 87 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 91 │ 146 │ 96 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 104 │ 117 │ 112 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3562976127351838\n",
- "- Feature index : 0, feature importance : 0.34647866842920744\n",
- "- Feature index : 2, feature importance : 0.29722371883560883\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.011459171975729987[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef0090>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5335335335335335\n",
- "\t\t- Score on test : 0.5265265265265265\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 176 │ 66 │ 91 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 68 │ 196 │ 69 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 85 │ 94 │ 154 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t2 <= 7.884028673171997\n",
- "Feature importances : \n",
- "- Feature index : 2, feature importance : 0.6447773749986965\n",
- "- Feature index : 1, feature importance : 0.33021348399657524\n",
- "- Feature index : 0, feature importance : 0.025009141004728383\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.019449904997600242[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.4034034034034034\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 148 │ 92 │ 93 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 97 │ 142 │ 94 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 113 │ 107 │ 113 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 2, feature importance : 0.4052965135270534\n",
- "- Feature index : 0, feature importance : 0.3019369228937852\n",
- "- Feature index : 1, feature importance : 0.2927665635791614\n",
- "\n",
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- " Estimator error | Estimator weight\n",
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.03309051800169982[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef0090>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.9719719719719719\n",
- "\t\t- Score on test : 0.42742742742742745\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 159 │ 92 │ 82 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 84 │ 165 │ 84 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 107 │ 123 │ 103 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 2, feature importance : 0.3421568007018131\n",
- "- Feature index : 1, feature importance : 0.33521422052353367\n",
- "- Feature index : 0, feature importance : 0.3226289787746533\n",
- "\n",
- "Done:\t Saving results\n",
- "Done:\t monoview benchmark\n",
- "Start:\t multiview arguments initialization\n",
- "Done:\t multiview arguments initialization\n",
- "Start:\t multiview benchmark\n",
- "Done:\t multiview benchmark\n",
- "Start:\t Analyzing all results\n",
- "Start:\t Score graph generation for accuracy_score*\n",
- "Done:\t Score graph generation for accuracy_score*\n",
- "Start:\t Label analysis figure generation\n",
- "locator: <matplotlib.ticker.FixedLocator object at 0x7f285452a9e8>\n",
- "Using fixed locator on colorbar\n",
- "Setting pcolormesh\n",
- "Done:\t Label analysis figures generation\n",
- "Done:\t Analyzing all results\n",
- "Start:\t Benchmark initialization\n",
- "Done:\t Benchmark initialization\n",
- "Start:\t monoview benchmark\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.011741251015337184[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef0240>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5325325325325325\n",
- "\t\t- Score on test : 0.5335335335335335\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 200 │ 69 │ 64 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 89 │ 160 │ 84 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 82 │ 78 │ 173 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t0 <= -7.5858564376831055\n",
- "Feature importances : \n",
- "- Feature index : 0, feature importance : 0.6426433328407938\n",
- "- Feature index : 1, feature importance : 0.30316084666342147\n",
- "- Feature index : 2, feature importance : 0.05419582049578462\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.016791434987680987[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.40540540540540543\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 132 │ 116 │ 85 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 83 │ 118 │ 132 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 80 │ 98 │ 155 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 0, feature importance : 0.3508179004161926\n",
- "- Feature index : 2, feature importance : 0.32829579432960804\n",
- "- Feature index : 1, feature importance : 0.32088630525419937\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
- "0.0 | 1.0\n",
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- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.032099153992021456[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef0240>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.9669669669669669\n",
- "\t\t- Score on test : 0.43043043043043044\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 167 │ 105 │ 61 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 117 │ 127 │ 89 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 97 │ 100 │ 136 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.34184835381666784\n",
- "- Feature index : 2, feature importance : 0.3331618840021268\n",
- "- Feature index : 0, feature importance : 0.32498976218120545\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.009638071001973003[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef0240>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5495495495495496\n",
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- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 201 │ 67 │ 65 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 69 │ 200 │ 64 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 97 │ 78 │ 158 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= -0.01163482666015625\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.5811118664011568\n",
- "- Feature index : 0, feature importance : 0.3003951272452718\n",
- "- Feature index : 2, feature importance : 0.11849300635357148\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.01566211401950568[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.42742742742742745\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 146 │ 98 │ 89 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 82 │ 152 │ 99 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 99 │ 105 │ 129 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3440774761871894\n",
- "- Feature index : 2, feature importance : 0.32910202407068434\n",
- "- Feature index : 0, feature importance : 0.32682049974212624\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.04119984098360874[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef0240>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.972972972972973\n",
- "\t\t- Score on test : 0.4624624624624625\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 181 │ 70 │ 82 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 97 │ 147 │ 89 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 116 │ 83 │ 134 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3553546874072236\n",
- "- Feature index : 0, feature importance : 0.33659333713048306\n",
- "- Feature index : 2, feature importance : 0.3080519754622934\n",
- "\n"
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.012263860990060493[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef0240>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5135135135135135\n",
- "\t\t- Score on test : 0.5625625625625625\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 210 │ 60 │ 63 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 72 │ 195 │ 66 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 96 │ 80 │ 157 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= -8.781835556030273\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.5759472379681086\n",
- "- Feature index : 0, feature importance : 0.34644073405667825\n",
- "- Feature index : 2, feature importance : 0.07761202797521309\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.019346140994457528[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.3923923923923924\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 142 │ 80 │ 111 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 101 │ 134 │ 98 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 111 │ 106 │ 116 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 0, feature importance : 0.36158644685294766\n",
- "- Feature index : 2, feature importance : 0.3203572874470783\n",
- "- Feature index : 1, feature importance : 0.31805626569997403\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
- "0.0 | 1.0\n",
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- "1.0 | 0.0\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.04268411098746583[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef0240>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.973973973973974\n",
- "\t\t- Score on test : 0.42342342342342343\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 149 │ 87 │ 97 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 86 │ 155 │ 92 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 102 │ 112 │ 119 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3600675330402482\n",
- "- Feature index : 0, feature importance : 0.327724535703172\n",
- "- Feature index : 2, feature importance : 0.3122079312565798\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.012006058008410037[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef0240>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5205205205205206\n",
- "\t\t- Score on test : 0.5365365365365365\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 188 │ 70 │ 75 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 62 │ 186 │ 85 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 88 │ 83 │ 162 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t2 <= 7.621823072433472\n",
- "Feature importances : \n",
- "- Feature index : 2, feature importance : 0.6127253529075672\n",
- "- Feature index : 1, feature importance : 0.3276148589893498\n",
- "- Feature index : 0, feature importance : 0.059659788103082985\n",
- "\n"
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- {
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.017790345998946577[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.3783783783783784\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 116 │ 105 │ 112 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 93 │ 133 │ 107 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 99 │ 105 │ 129 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 2, feature importance : 0.3798342367122621\n",
- "- Feature index : 1, feature importance : 0.3163714597070011\n",
- "- Feature index : 0, feature importance : 0.3037943035807368\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.03771343201515265[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef0240>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.973973973973974\n",
- "\t\t- Score on test : 0.44344344344344344\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 159 │ 90 │ 84 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 74 │ 157 │ 102 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 108 │ 98 │ 127 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3367546219487557\n",
- "- Feature index : 2, feature importance : 0.3361012156655226\n",
- "- Feature index : 0, feature importance : 0.32714416238572175\n",
- "\n",
- "Done:\t Saving results\n",
- "Done:\t monoview benchmark\n",
- "Start:\t multiview arguments initialization\n",
- "Done:\t multiview arguments initialization\n",
- "Start:\t multiview benchmark\n",
- "Done:\t multiview benchmark\n",
- "Start:\t Analyzing all results\n",
- "Start:\t Score graph generation for accuracy_score*\n",
- "Done:\t Score graph generation for accuracy_score*\n",
- "Start:\t Label analysis figure generation\n",
- "locator: <matplotlib.ticker.FixedLocator object at 0x7f28546ae2e8>\n",
- "Using fixed locator on colorbar\n",
- "Setting pcolormesh\n",
- "Done:\t Label analysis figures generation\n",
- "Done:\t Analyzing all results\n",
- "Start:\t Benchmark initialization\n",
- "Done:\t Benchmark initialization\n",
- "Start:\t monoview benchmark\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.017450111015932634[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef0318>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5435435435435435\n",
- "\t\t- Score on test : 0.5315315315315315\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 201 │ 70 │ 62 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 91 │ 143 │ 99 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 71 │ 75 │ 187 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t0 <= -7.537216424942017\n",
- "Feature importances : \n",
- "- Feature index : 0, feature importance : 0.5226051614948145\n",
- "- Feature index : 1, feature importance : 0.34315504101576955\n",
- "- Feature index : 2, feature importance : 0.13423979748941609\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n"
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- "text": [
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.03680643701227382[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.38538538538538536\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 124 │ 110 │ 99 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 102 │ 120 │ 111 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 81 │ 111 │ 141 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 0, feature importance : 0.38824868202962015\n",
- "- Feature index : 2, feature importance : 0.30630942653599513\n",
- "- Feature index : 1, feature importance : 0.30544189143438477\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
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- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.04335637201438658[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef0318>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.972972972972973\n",
- "\t\t- Score on test : 0.4014014014014014\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 147 │ 113 │ 73 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 126 │ 126 │ 81 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 91 │ 114 │ 128 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3531902456622059\n",
- "- Feature index : 0, feature importance : 0.35014010054650957\n",
- "- Feature index : 2, feature importance : 0.2966696537912845\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.01579122498515062[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef0318>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5695695695695696\n",
- "\t\t- Score on test : 0.5305305305305306\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 189 │ 84 │ 60 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 68 │ 192 │ 73 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 79 │ 105 │ 149 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= -8.038341045379639\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.46117819456772075\n",
- "- Feature index : 0, feature importance : 0.40154750850939563\n",
- "- Feature index : 2, feature importance : 0.13727429692288373\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.033786593994591385[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.3933933933933934\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 133 │ 86 │ 114 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 92 │ 136 │ 105 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 96 │ 113 │ 124 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 0, feature importance : 0.35097011165256853\n",
- "- Feature index : 1, feature importance : 0.32608433124358605\n",
- "- Feature index : 2, feature importance : 0.3229455571038454\n",
- "\n",
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- " Estimator error | Estimator weight\n",
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
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- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
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- "Start:\t Training\n",
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- "Info:\t Duration for training and predicting: 0.08894029300427064[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with random_forest.\n",
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- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef0318>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.972972972972973\n",
- "\t\t- Score on test : 0.44644644644644643\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 174 │ 77 │ 82 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 94 │ 145 │ 94 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 101 │ 105 │ 127 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3537167189738878\n",
- "- Feature index : 0, feature importance : 0.3392257345584697\n",
- "- Feature index : 2, feature importance : 0.30705754646764255\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.016797334974398836[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef0318>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5455455455455456\n",
- "\t\t- Score on test : 0.5375375375375375\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 185 │ 80 │ 68 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 69 │ 189 │ 75 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 79 │ 91 │ 163 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= -8.3212308883667\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.6531314724862579\n",
- "- Feature index : 0, feature importance : 0.3214686025048021\n",
- "- Feature index : 2, feature importance : 0.02539992500894002\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.02450905999285169[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.3943943943943944\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 147 │ 90 │ 96 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 92 │ 111 │ 130 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 107 │ 90 │ 136 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3983423348078147\n",
- "- Feature index : 0, feature importance : 0.3424457373272194\n",
- "- Feature index : 2, feature importance : 0.25921192786496594\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
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- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.045477173989638686[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef0318>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.96996996996997\n",
- "\t\t- Score on test : 0.4164164164164164\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 151 │ 93 │ 89 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 91 │ 143 │ 99 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 105 │ 106 │ 122 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.37412853003104596\n",
- "- Feature index : 0, feature importance : 0.3262055843514551\n",
- "- Feature index : 2, feature importance : 0.2996658856174991\n",
- "\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.01210012601222843[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef0318>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5315315315315315\n",
- "\t\t- Score on test : 0.5335335335335335\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 196 │ 68 │ 69 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 69 │ 193 │ 71 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 86 │ 103 │ 144 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= 0.19560027122497559\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.6775639173831282\n",
- "- Feature index : 0, feature importance : 0.3224360826168718\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.01731816300889477[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.3863863863863864\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 139 │ 83 │ 111 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 84 │ 126 │ 123 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 98 │ 114 │ 121 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.38233804155148937\n",
- "- Feature index : 0, feature importance : 0.3479529817784296\n",
- "- Feature index : 2, feature importance : 0.2697089766700809\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
- "0.0 | 1.0\n",
- "1.0 | 0.0\n",
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- "1.0 | 0.0\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.034021465020487085[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef0318>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.9719719719719719\n",
- "\t\t- Score on test : 0.45245245245245247\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 174 │ 68 │ 91 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 88 │ 153 │ 92 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 104 │ 104 │ 125 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.34515048305515383\n",
- "- Feature index : 2, feature importance : 0.338274110741391\n",
- "- Feature index : 0, feature importance : 0.3165754062034552\n",
- "\n",
- "Done:\t Saving results\n",
- "Done:\t monoview benchmark\n",
- "Start:\t multiview arguments initialization\n",
- "Done:\t multiview arguments initialization\n",
- "Start:\t multiview benchmark\n",
- "Done:\t multiview benchmark\n",
- "Start:\t Analyzing all results\n",
- "Start:\t Score graph generation for accuracy_score*\n",
- "Done:\t Score graph generation for accuracy_score*\n",
- "Start:\t Label analysis figure generation\n",
- "locator: <matplotlib.ticker.FixedLocator object at 0x7f2851c7db38>\n",
- "Using fixed locator on colorbar\n",
- "Setting pcolormesh\n",
- "Done:\t Label analysis figures generation\n",
- "Done:\t Analyzing all results\n",
- "Start:\t Benchmark initialization\n",
- "Done:\t Benchmark initialization\n",
- "Start:\t monoview benchmark\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.017685680009890348[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef02d0>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5515515515515516\n",
- "\t\t- Score on test : 0.5195195195195195\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 194 │ 61 │ 78 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 93 │ 152 │ 88 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 72 │ 88 │ 173 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t0 <= -7.537216424942017\n",
- "Feature importances : \n",
- "- Feature index : 0, feature importance : 0.6227376471820618\n",
- "- Feature index : 1, feature importance : 0.30032813402069375\n",
- "- Feature index : 2, feature importance : 0.07693421879724446\n",
- "\n"
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- "name": "stderr",
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.024542364990338683[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.40540540540540543\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 135 │ 98 │ 100 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 109 │ 129 │ 95 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 87 │ 105 │ 141 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 0, feature importance : 0.3635255671687931\n",
- "- Feature index : 2, feature importance : 0.3210206934913345\n",
- "- Feature index : 1, feature importance : 0.3154537393398723\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_1 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.06806946799042635[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_1 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_1\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef02d0>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.970970970970971\n",
- "\t\t- Score on test : 0.43343343343343343\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 169 │ 81 │ 83 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 125 │ 132 │ 76 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 99 │ 102 │ 132 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 2, feature importance : 0.343736464289811\n",
- "- Feature index : 1, feature importance : 0.33857188774317215\n",
- "- Feature index : 0, feature importance : 0.3176916479670169\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.023136607982451096[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef02d0>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5595595595595596\n",
- "\t\t- Score on test : 0.5385385385385385\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 183 │ 59 │ 91 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 59 │ 191 │ 83 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 81 │ 88 │ 164 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= 0.3691229820251465\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.5468384818929156\n",
- "- Feature index : 0, feature importance : 0.3808963789533876\n",
- "- Feature index : 2, feature importance : 0.07226513915369666\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.021909513015998527[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_2\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.4244244244244244\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 150 │ 83 │ 100 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 87 │ 141 │ 105 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 90 │ 110 │ 133 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3720066821591741\n",
- "- Feature index : 0, feature importance : 0.33594054790107486\n",
- "- Feature index : 2, feature importance : 0.29205276993975093\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
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- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_2 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
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- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
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- "Info:\t Duration for training and predicting: 0.05181503898347728[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_2 with random_forest.\n",
- "\n",
- "Database configuration : \n",
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- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 162 │ 84 │ 87 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 85 │ 166 │ 82 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 107 │ 106 │ 120 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3548025856213372\n",
- "- Feature index : 0, feature importance : 0.32827612799964195\n",
- "- Feature index : 2, feature importance : 0.31692128637902084\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.014254659996367991[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef02d0>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5625625625625625\n",
- "\t\t- Score on test : 0.5245245245245245\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 190 │ 65 │ 78 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 67 │ 187 │ 79 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 90 │ 96 │ 147 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t1 <= -1.1706411838531494\n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.5090799830467423\n",
- "- Feature index : 0, feature importance : 0.4909200169532578\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.01773965498432517[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.38238238238238237\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 115 │ 79 │ 139 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 91 │ 129 │ 113 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 100 │ 95 │ 138 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.37763966614448174\n",
- "- Feature index : 0, feature importance : 0.33320078029807343\n",
- "- Feature index : 2, feature importance : 0.28915955355744494\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
- "0.0 | 1.0\n",
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- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
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- "1.0 | 0.0\n",
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- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_3 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.048221231991192326[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_3 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_3\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef02d0>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.965965965965966\n",
- "\t\t- Score on test : 0.42542542542542544\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 149 │ 82 │ 102 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 85 │ 158 │ 90 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 104 │ 111 │ 118 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 1, feature importance : 0.3683595717213061\n",
- "- Feature index : 0, feature importance : 0.3373841287612923\n",
- "- Feature index : 2, feature importance : 0.29425629951740156\n",
- "\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : decision_tree\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.012050641991663724[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with decision_tree.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- DecisionTree with max_depth : 3, criterion : gini, splitter : best, random_state : <mtrand.RandomState object at 0x7f2859ef02d0>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.5645645645645646\n",
- "\t\t- Score on test : 0.5005005005005005\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 177 │ 73 │ 83 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 67 │ 193 │ 73 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 96 │ 107 │ 130 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "First featrue : \n",
- "\t2 <= 5.844297647476196\n",
- "Feature importances : \n",
- "- Feature index : 2, feature importance : 0.5868595382863983\n",
- "- Feature index : 1, feature importance : 0.3312062534941445\n",
- "- Feature index : 0, feature importance : 0.08193420821945724\n",
- "\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : adaboost\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.018854184017982334[s]\n",
- "Start:\t Getting results\n",
- "/home/baptiste/Documents/venvs/develop/lib/python3.6/site-packages/sklearn/base.py:197: FutureWarning:\n",
- "\n",
- "From version 0.24, get_params will raise an AttributeError if a parameter cannot be retrieved as an instance attribute. Previously it would return None.\n",
- "\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with adaboost.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- Adaboost with n_estimators : 50, base_estimator : DecisionTreeClassifier\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 1.0\n",
- "\t\t- Score on test : 0.3813813813813814\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 115 │ 118 │ 100 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 98 │ 146 │ 89 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 97 │ 116 │ 120 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 2, feature importance : 0.34580735025180703\n",
- "- Feature index : 0, feature importance : 0.332606265184098\n",
- "- Feature index : 1, feature importance : 0.32158638456409483\n",
- "\n",
- "\n",
- " Estimator error | Estimator weight\n",
- "0.0 | 1.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
- "1.0 | 0.0\n",
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- "1.0 | 0.0\n",
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- "1.0 | 0.0\n",
- "Done:\t Saving results\n",
- "Start:\t Loading data\n",
- "Done:\t Loading data\n",
- "Info:\t Classification - Database:tuto View:generated_view_4 train ratio:0.5, CrossValidation k-folds: 5, cores:1, algorithm : random_forest\n",
- "Start:\t Determine Train/Test split\n",
- "Info:\t Shape X_train:(999, 3), Length of y_train:999\n",
- "Info:\t Shape X_test:(999, 3), Length of y_test:999\n",
- "Done:\t Determine Train/Test split\n",
- "Start:\t Generate classifier args\n",
- "Done:\t Generate classifier args\n",
- "Start:\t Training\n",
- "Done:\t Training\n",
- "Start:\t Predicting\n",
- "Done:\t Predicting\n",
- "Info:\t Duration for training and predicting: 0.04730147498776205[s]\n",
- "Start:\t Getting results\n",
- "Done:\t Getting results\n",
- "Start:\t Saving preds\n",
- "Classification on tuto for generated_view_4 with random_forest.\n",
- "\n",
- "Database configuration : \n",
- "\t- Database name : tuto\n",
- "\t- View name : generated_view_4\t View shape : (1998, 3)\n",
- "\t- Learning Rate : 0.5\n",
- "\t- Labels used : label_1, label_2, label_3\n",
- "\t- Number of cross validation folds : 5\n",
- "\n",
- "Classifier configuration : \n",
- "\t- RandomForest with n_estimators : 10, max_depth : None, criterion : gini, random_state : <mtrand.RandomState object at 0x7f2859ef02d0>\n",
- "\t- Executed on 1 core(s) \n",
- "\n",
- "\n",
- "\tFor Accuracy score using {}, (higher is better) : \n",
- "\t\t- Score on train : 0.980980980980981\n",
- "\t\t- Score on test : 0.44244244244244246\n",
- "\n",
- "Test set confusion matrix : \n",
- "\n",
- "╒═════════╤═══════════╤═══════════╤═══════════╕\n",
- "│ │ label_1 │ label_2 │ label_3 │\n",
- "╞═════════╪═══════════╪═══════════╪═══════════╡\n",
- "│ label_1 │ 162 │ 77 │ 94 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_2 │ 86 │ 151 │ 96 │\n",
- "├─────────┼───────────┼───────────┼───────────┤\n",
- "│ label_3 │ 107 │ 97 │ 129 │\n",
- "╘═════════╧═══════════╧═══════════╧═══════════╛\n",
- "\n",
- "\n",
- "\n",
- " Classification took 0:00:00\n",
- "\n",
- " Classifier Interpretation : \n",
- "Feature importances : \n",
- "- Feature index : 2, feature importance : 0.3401685694795628\n",
- "- Feature index : 1, feature importance : 0.3401340580160968\n",
- "- Feature index : 0, feature importance : 0.3196973725043405\n",
- "\n",
- "Done:\t Saving results\n",
- "Done:\t monoview benchmark\n",
- "Start:\t multiview arguments initialization\n",
- "Done:\t multiview arguments initialization\n",
- "Start:\t multiview benchmark\n",
- "Done:\t multiview benchmark\n",
- "Start:\t Analyzing all results\n",
- "Start:\t Score graph generation for accuracy_score*\n",
- "Done:\t Score graph generation for accuracy_score*\n",
- "Start:\t Label analysis figure generation\n",
- "locator: <matplotlib.ticker.FixedLocator object at 0x7f2852ff4a20>\n",
- "Using fixed locator on colorbar\n",
- "Setting pcolormesh\n",
- "Done:\t Label analysis figures generation\n",
- "Done:\t Analyzing all results\n",
- "Done:\t Executing all the needed benchmarks\n",
- "Start:\t Analyzing predictions\n",
- "Start:\t Analyzing all results\n",
- "Start:\t Score graph generation for accuracy_score*\n",
- "Done:\t Score graph generation for accuracy_score*\n",
- "Start:\t Label analysis figure generation\n",
- "locator: <matplotlib.ticker.FixedLocator object at 0x7f2852cf5240>\n",
- "Using fixed locator on colorbar\n",
- "Setting pcolormesh\n",
- "Done:\t Label analysis figures generation\n",
- "Start:\t Score graph generation for accuracy_score*\n",
- "Done:\t Score graph generation for accuracy_score*\n",
- "Start:\t Label analysis figure generation\n",
- "locator: <matplotlib.ticker.FixedLocator object at 0x7f2852ceb860>\n",
- "Using fixed locator on colorbar\n",
- "Setting pcolormesh\n",
- "Done:\t Label analysis figures generation\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Start:\t Score graph generation for accuracy_score*\n",
- "Done:\t Score graph generation for accuracy_score*\n",
- "Start:\t Label analysis figure generation\n",
- "locator: <matplotlib.ticker.FixedLocator object at 0x7f28553bcf28>\n",
- "Using fixed locator on colorbar\n",
- "Setting pcolormesh\n",
- "Done:\t Label analysis figures generation\n",
- "Start:\t Score graph generation for accuracy_score*\n",
- "Done:\t Score graph generation for accuracy_score*\n",
- "Start:\t Label analysis figure generation\n",
- "locator: <matplotlib.ticker.FixedLocator object at 0x7f28531a7400>\n",
- "Using fixed locator on colorbar\n",
- "Setting pcolormesh\n",
- "Done:\t Label analysis figures generation\n",
- "Start:\t Score graph generation for accuracy_score*\n",
- "Done:\t Score graph generation for accuracy_score*\n",
- "Start:\t Label analysis figure generation\n",
- "locator: <matplotlib.ticker.FixedLocator object at 0x7f285329fef0>\n",
- "Using fixed locator on colorbar\n",
- "Setting pcolormesh\n",
- "Done:\t Label analysis figures generation\n",
- "Done:\t Analyzing all results\n",
- "Start:\t Global label analysis figure generation\n",
- "locator: <matplotlib.ticker.FixedLocator object at 0x7f28532cf8d0>\n",
- "Using fixed locator on colorbar\n",
- "Setting pcolormesh\n",
- "Done:\t Global label analysis figures generation\n",
- "Done:\t Analyzing predictions\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"from multiview_platform.execute import execute \n",
"\n",
@@ -5194,7 +228,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 7,
"metadata": {
"pycharm": {
"is_executing": false
@@ -5208,17 +242,17 @@
" <iframe\n",
" width=\"900\"\n",
" height=\"500\"\n",
- " src=\"supplementary_material/tuto/started_2020_04_22-09_19_/error_analysis_2D.html\"\n",
+ " src=\"supplementary_material/tuto/started_2020_04_29-09_36_/error_analysis_2D.html\"\n",
" frameborder=\"0\"\n",
" allowfullscreen\n",
" ></iframe>\n",
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7f2855665fd0>"
+ "<IPython.lib.display.IFrame at 0x7f71927ec9e8>"
]
},
- "execution_count": 6,
+ "execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
diff --git a/demo/tutorials/sub_problems_configuration.ipynb b/demo/tutorials/sub_problems_configuration.ipynb
index 2aa0d6d..1b591e3 100644
--- a/demo/tutorials/sub_problems_configuration.ipynb
+++ b/demo/tutorials/sub_problems_configuration.ipynb
@@ -3979,20 +3979,20 @@
"<div>\n",
" \n",
" \n",
- " <div id=\"e813c15e-86c1-40a0-93ac-334e7c8875de\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
+ " <div id=\"a98932b8-ee46-41b2-ab6d-8b9565b361af\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
" <script type=\"text/javascript\">\n",
" require([\"plotly\"], function(Plotly) {\n",
" window.PLOTLYENV=window.PLOTLYENV || {};\n",
" \n",
- " if (document.getElementById(\"e813c15e-86c1-40a0-93ac-334e7c8875de\")) {\n",
+ " if (document.getElementById(\"a98932b8-ee46-41b2-ab6d-8b9565b361af\")) {\n",
" Plotly.newPlot(\n",
- " 'e813c15e-86c1-40a0-93ac-334e7c8875de',\n",
+ " 'a98932b8-ee46-41b2-ab6d-8b9565b361af',\n",
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GitLab