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Weight0samples error (#23)

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* Add Hyperparameters description to README
Comment get_subspace method
Add environment info for binder (runtime.txt)

* Complete source comments
Change docstring type to numpy
update hyperameters table and explanation

* Fix problem with zero weighted samples
Solve WARNING: class label x specified in weight is not found
with a different approach

* Allow update of scikitlearn to latest version
This commit is contained in:
Ricardo Montañana Gómez
2021-01-19 11:40:46 +01:00
committed by GitHub
parent 3bdac9bd60
commit 147dad684c
4 changed files with 31 additions and 43 deletions
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14
stree/Strees.py
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@@ -629,6 +629,12 @@ class Stree(BaseEstimator, ClassifierMixin):
"""
if depth > self.__max_depth:
return None
# Mask samples with 0 weight
if any(sample_weight == 0):
indices_zero = sample_weight == 0
X = X[~indices_zero, :]
y = y[~indices_zero]
sample_weight = sample_weight[~indices_zero]
if np.unique(y).shape[0] == 1:
# only 1 class => pure dataset
return Snode(
@@ -643,14 +649,6 @@ class Stree(BaseEstimator, ClassifierMixin):
# Train the model
clf = self._build_clf()
Xs, features = self.splitter_.get_subspace(X, y, self.max_features_)
# solve WARNING: class label 0 specified in weight is not found
# in bagging
if any(sample_weight == 0):
indices = sample_weight == 0
y_next = y[~indices]
# touch weights if removing any class
if np.unique(y_next).shape[0] != self.n_classes_:
sample_weight += 1e-5
clf.fit(Xs, y, sample_weight=sample_weight)
impurity = self.splitter_.partition_impurity(y)
node = Snode(clf, X, y, features, impurity, title, sample_weight)