From 96d4fef67f15062b7a1a307f9e5fe57509f66853 Mon Sep 17 00:00:00 2001
From: Dominique Benielli <dominique.benielli@lis-lab.fr>
Date: Thu, 16 Jan 2020 14:47:42 +0100
Subject: [PATCH] test passed
---
multimodal/boosting/cumbo.py | 18 ++++++++++++------
1 file changed, 12 insertions(+), 6 deletions(-)
diff --git a/multimodal/boosting/cumbo.py b/multimodal/boosting/cumbo.py
index 0d7eb4d..55a07f9 100644
--- a/multimodal/boosting/cumbo.py
+++ b/multimodal/boosting/cumbo.py
@@ -113,23 +113,29 @@ class MuCumboClassifier(BaseEnsemble, ClassifierMixin, UBoosting):
>>> views_ind = [0, 2, 4] # view 0: sepal data, view 1: petal data
>>> clf = MuCumboClassifier(random_state=0)
>>> clf.fit(X, y, views_ind) # doctest: +NORMALIZE_WHITESPACE
-
+ MuCumboClassifier(base_estimator=None, n_estimators=50, random_state=0)
>>> print(clf.predict([[ 5., 3., 1., 1.]]))
- [1]
+ [0]
>>> views_ind = [[0, 2], [1, 3]] # view 0: length data, view 1: width data
>>> clf = MuCumboClassifier(random_state=0)
>>> clf.fit(X, y, views_ind) # doctest: +NORMALIZE_WHITESPACE
-
+ MuCumboClassifier(base_estimator=None, n_estimators=50, random_state=0)
>>> print(clf.predict([[ 5., 3., 1., 1.]]))
- [1]
+ [0]
>>> from sklearn.tree import DecisionTreeClassifier
>>> base_estimator = DecisionTreeClassifier(max_depth=2)
>>> clf = MuCumboClassifier(base_estimator=base_estimator, random_state=0)
>>> clf.fit(X, y, views_ind) # doctest: +NORMALIZE_WHITESPACE
-
+ MuCumboClassifier(base_estimator=DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=2,
+ max_features=None, max_leaf_nodes=None,
+ min_impurity_decrease=0.0, min_impurity_split=None,
+ min_samples_leaf=1, min_samples_split=2,
+ min_weight_fraction_leaf=0.0, presort=False, random_state=None,
+ splitter='best'),
+ n_estimators=50, random_state=0)
>>> print(clf.predict([[ 5., 3., 1., 1.]]))
- [1]
+ [0]
See also
--------
--
GitLab