From d5f2b26b158b1b8f4efb46dd42d44fa4357018e7 Mon Sep 17 00:00:00 2001
From: Baptiste Bauvin <baptiste.bauvin@lis-lab.fr>
Date: Tue, 22 Mar 2022 11:15:53 -0400
Subject: [PATCH] Added feature relevance
---
.../result_analysis/execution.py | 4 ++--
.../result_analysis/feature_importances.py | 22 +++++++++++++++++--
2 files changed, 22 insertions(+), 4 deletions(-)
diff --git a/summit/multiview_platform/result_analysis/execution.py b/summit/multiview_platform/result_analysis/execution.py
index 279891e7..7e046df7 100644
--- a/summit/multiview_platform/result_analysis/execution.py
+++ b/summit/multiview_platform/result_analysis/execution.py
@@ -84,7 +84,7 @@ def analyze_iterations(results, benchmark_argument_dictionaries, stats_iter,
sample_errors = get_sample_errors(labels, result)
feature_importances = get_feature_importances(result,
feature_ids=feature_ids,
- view_names=view_names)
+ view_names=view_names,)
durations = get_duration(result)
directory = arguments["directory"]
@@ -98,7 +98,7 @@ def analyze_iterations(results, benchmark_argument_dictionaries, stats_iter,
publish_sample_errors(sample_errors, directory, database_name,
labels_names, sample_ids, labels)
publish_feature_importances(feature_importances, directory,
- database_name)
+ database_name, metric_scores=metrics_scores)
plot_durations(durations, directory, database_name)
iter_results["metrics_scores"][iter_index] = metrics_scores
diff --git a/summit/multiview_platform/result_analysis/feature_importances.py b/summit/multiview_platform/result_analysis/feature_importances.py
index c3f234f6..0735c6ea 100644
--- a/summit/multiview_platform/result_analysis/feature_importances.py
+++ b/summit/multiview_platform/result_analysis/feature_importances.py
@@ -7,7 +7,7 @@ import plotly
from ..monoview.monoview_utils import MonoviewResult
-def get_feature_importances(result, feature_ids=None, view_names=None):
+def get_feature_importances(result, feature_ids=None, view_names=None,):
r"""Extracts the feature importance from the monoview results and stores
them in a dictionnary :
feature_importance[view_name] is a pandas.DataFrame of size n_feature*n_clf
@@ -49,7 +49,7 @@ def get_feature_importances(result, feature_ids=None, view_names=None):
def publish_feature_importances(feature_importances, directory, database_name,
- feature_stds=None): # pragma: no cover
+ feature_stds=None, metric_scores=None): # pragma: no cover
importance_dfs = []
std_dfs = []
if not os.path.exists(os.path.join(directory, "feature_importances")):
@@ -94,6 +94,9 @@ def publish_feature_importances(feature_importances, directory, database_name,
feature_std_df = pd.concat([feature_std_df, fake], axis=1,).fillna(0)
plot_feature_importances(os.path.join(directory, "feature_importances",
database_name), feature_importances_df, feature_std_df)
+ if metric_scores is not None:
+ plot_feature_relevance(os.path.join(directory, "feature_importances",
+ database_name), feature_importances_df, feature_std_df, metric_scores)
def plot_feature_importances(file_name, feature_importance,
@@ -125,3 +128,18 @@ def plot_feature_importances(file_name, feature_importance,
plotly.offline.plot(fig, filename=file_name + ".html", auto_open=False)
del fig
+
+
+def plot_feature_relevance(file_name, feature_importance,
+ feature_std, metric_scores): # pragma: no cover
+ for metric, score_df in metric_scores.items():
+ if metric.endswith("*"):
+ for score in score_df.columns:
+ if len(score.split("-"))>1:
+ algo, view = score.split("-")
+ feature_importance[algo].loc[[ind for ind in feature_importance.index if ind.startswith(view)]]*=score_df[score]['test']
+ else:
+ feature_importance[score] *= score_df[score]['test']
+ file_name+="_relevance"
+ plot_feature_importances(file_name, feature_importance,
+ feature_std)
--
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