8000 [MRG+1] FIX Add missing mixins to ClassifierChain by jnothman · Pull Request #9473 · scikit-learn/scikit-learn · GitHub
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[MRG+1] FIX Add missing mixins to ClassifierChain #9473

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Merged
merged 2 commits into from
Aug 4, 2017
Merged

[MRG+1] FIX Add missing mixins to ClassifierChain #9473

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1322f1c
Add missing mixins to ClassifierChain
jnothman Aug 1, 2017
0377924
Fix import in test
jnothman Aug 2, 2017
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2 changes: 1 addition & 1 deletion sklearn/multioutput.py
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Original file line number Diff line number Diff line change
Expand Up @@ -368,7 +368,7 @@ def score(self, X, y):
return np.mean(np.all(y == y_pred, axis=1))


class ClassifierChain(BaseEstimator):
class ClassifierChain(BaseEstimator, ClassifierMixin, MetaEstimatorMixin):
"""A multi-label model that arranges binary classifiers into a chain.

Each model makes a prediction in the order specified by the chain using
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3 changes: 3 additions & 0 deletions sklearn/tests/test_multioutput.py
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Expand Up @@ -29,6 +29,7 @@
from sklearn.multioutput import MultiOutputClassifier
from sklearn.multioutput import MultiOutputRegressor
from sklearn.svm import LinearSVC
from sklearn.base import ClassifierMixin
from sklearn.utils import shuffle


Expand Down Expand Up @@ -380,6 +381,8 @@ def test_classifier_chain_fit_and_predict_with_logistic_regression():
assert_equal([c.coef_.size for c in classifier_chain.estimators_],
list(range(X.shape[1], X.shape[1] + Y.shape[1])))

assert isinstance(classifier_chain, ClassifierMixin)
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In light of #9475, you should probably use is_classifier

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Not in a test assertion. The point here is that it also ensures a default implementation is score

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fair enough



def test_classifier_chain_fit_and_predict_with_linear_svc():
# Fit classifier chain and verify predict performance using LinearSVC
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