From 5d572966b1a724c2b33e60d9447e9ac1a81be18b Mon Sep 17 00:00:00 2001
From: Baptiste Bauvin <baptiste.bauvin@lis-lab.fr>
Date: Mon, 25 Nov 2019 13:19:58 -0500
Subject: [PATCH] None error in config file
---
config_files/config_test.yml | 12 ++++++------
.../multiview/exec_multiview.py | 1 -
.../weighted_linear_early_fusion.py | 4 +++-
3 files changed, 9 insertions(+), 8 deletions(-)
diff --git a/config_files/config_test.yml b/config_files/config_test.yml
index 9edf21a9..4969960b 100644
--- a/config_files/config_test.yml
+++ b/config_files/config_test.yml
@@ -1,7 +1,7 @@
# The base configuration of the benchmark
Base :
log: True
- name: ["control_vs_malade"]
+ name: ["plausible"]
label: "_"
type: ".hdf5"
views: ["300nm", "350nm"]
@@ -19,12 +19,12 @@ Base :
Classification:
multiclass_method: "oneVersusOne"
split: 0.4
- nb_folds: 5
+ nb_folds: 2
nb_class: 2
classes:
- type: ["monoview",]
+ type: ["multiview",]
algos_monoview: ["decision_tree"]
- algos_multiview: ["all"]
+ algos_multiview: ["weighted_linear_early_fusion"]
stats_iter: 2
metrics: ["accuracy_score", "f1_score"]
metric_princ: "f1_score"
@@ -123,7 +123,7 @@ gradient_boosting:
######################################
weighted_linear_early_fusion:
- view_weights: [None]
+ view_weights: [null]
monoview_classifier_name: ["decision_tree"]
monoview_classifier_config:
decision_tree:
@@ -200,7 +200,7 @@ weighted_linear_late_fusion:
splitter: ["best"]
mumbo:
- base_estimator: [None]
+ base_estimator: [null]
n_estimators: [10]
best_view_mode: ["edge"]
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py b/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py
index b5020c21..761a970d 100644
--- a/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py
@@ -264,7 +264,6 @@ def exec_multiview(directory, dataset_var, name, classification_indices, k_folds
logging.debug("Start:\t Optimizing hyperparameters")
if hyper_param_search != "None":
- print(metrics)
classifier_config = hyper_parameter_search.search_best_settings(
dataset_var, labels, classifier_module, classifier_name,
metrics[0], learning_indices, k_folds, random_state,
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/weighted_linear_early_fusion.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/weighted_linear_early_fusion.py
index 159623e4..e8437154 100644
--- a/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/weighted_linear_early_fusion.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/weighted_linear_early_fusion.py
@@ -31,7 +31,7 @@ class WeightedLinearEarlyFusion(BaseMultiviewClassifier, BaseFusionClassifier):
def __init__(self, random_state=None, view_weights=None,
monoview_classifier_name="decision_tree",
monoview_classifier_config={}):
-
+ print(type(view_weights), view_weights)
super(WeightedLinearEarlyFusion, self).__init__(random_state=random_state)
self.view_weights = view_weights
self.monoview_classifier_name = monoview_classifier_name
@@ -84,10 +84,12 @@ class WeightedLinearEarlyFusion(BaseMultiviewClassifier, BaseFusionClassifier):
example_indices, self.view_indices = get_examples_views_indices(dataset,
example_indices,
view_indices)
+ print(type(self.view_weights))
if self.view_weights is None:
self.view_weights = np.ones(len(self.view_indices), dtype=float)
else:
self.view_weights = np.array(self.view_weights)
+ print(self.view_weights)
self.view_weights /= float(np.sum(self.view_weights))
X = self.hdf5_to_monoview(dataset, example_indices)
--
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