From d2326aa71ed25c8e5dc6ffe89494b9c00dc10f90 Mon Sep 17 00:00:00 2001
From: Baptiste Bauvin <baptiste.bauvin@lis-lab.fr>
Date: Thu, 9 Mar 2023 12:40:32 -0500
Subject: [PATCH] Feat_imp_works with nans
---
.../monoview_classifiers/ib_svm_rbf.py | 3 +-
.../monoview_classifiers/random_foscm.py | 45 +++++++++++++++++++
2 files changed, 47 insertions(+), 1 deletion(-)
create mode 100644 summit/multiview_platform/monoview_classifiers/random_foscm.py
diff --git a/summit/multiview_platform/monoview_classifiers/ib_svm_rbf.py b/summit/multiview_platform/monoview_classifiers/ib_svm_rbf.py
index 095bc7dc..5f6305e5 100644
--- a/summit/multiview_platform/monoview_classifiers/ib_svm_rbf.py
+++ b/summit/multiview_platform/monoview_classifiers/ib_svm_rbf.py
@@ -32,7 +32,8 @@ class IBSVMRBF(BaseMonoviewClassifier, BalancedBaggingClassifier):
for estim in self.estimators_:
if hasattr(estim['classifier'], 'feature_importances_'):
self.feature_importances_ += estim['classifier'].feature_importances_
- self.feature_importances_ /= np.sum(self.feature_importances_)
+ if np.sum(self.feature_importances_)!=0:
+ self.feature_importances_ /= np.sum(self.feature_importances_)
return self
diff --git a/summit/multiview_platform/monoview_classifiers/random_foscm.py b/summit/multiview_platform/monoview_classifiers/random_foscm.py
new file mode 100644
index 00000000..202ac61b
--- /dev/null
+++ b/summit/multiview_platform/monoview_classifiers/random_foscm.py
@@ -0,0 +1,45 @@
+from sklearn.ensemble import RandomForestClassifier
+
+from ..monoview.monoview_utils import BaseMonoviewClassifier
+from summit.multiview_platform.utils.hyper_parameter_search import CustomRandint
+
+# Author-Info
+__author__ = "Baptiste Bauvin"
+__status__ = "Prototype" # Production, Development, Prototype
+
+classifier_class_name = "RandomForest"
+
+
+class RandomForest(RandomForestClassifier, BaseMonoviewClassifier):
+ """
+ This class is an adaptation of scikit-learn's `RandomForestClassifier <https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html>`_
+
+
+ """
+
+ def __init__(self, random_state=None, n_estimators=10,
+ max_depth=None, criterion='gini', **kwargs):
+
+ RandomForestClassifier.__init__(self,
+ n_estimators=n_estimators,
+ max_depth=max_depth,
+ criterion=criterion,
+ class_weight="balanced",
+ random_state=random_state
+ )
+ self.param_names = ["n_estimators", "max_depth", "criterion",
+ "random_state"]
+ self.classed_params = []
+ self.distribs = [CustomRandint(low=1, high=300),
+ CustomRandint(low=1, high=10),
+ ["gini", "entropy"], [random_state]]
+ self.weird_strings = {}
+
+ def get_interpretation(self, directory, base_file_name, y_test, feature_ids,
+ multiclass=False):
+
+ interpret_string = ""
+ interpret_string += self.get_feature_importance(directory,
+ base_file_name,
+ feature_ids)
+ return interpret_string
--
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