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Enable us to use sklearn to do cv for functional api #9320

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Merged
merged 4 commits into from
Feb 8, 2018
Merged

Enable us to use sklearn to do cv for functional api #9320

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c0a6bb8
enable us to use sklearn to do cv for functional api
XinsongDu Feb 6, 2018
8259f18
adjust code for multiclass
XinsongDu Feb 6, 2018
8dd4258
remove tailing space
XinsongDu Feb 6, 2018
3b94ff1
remove irrelevant comment
XinsongDu Feb 8, 2018
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10 changes: 8 additions & 2 deletions keras/wrappers/scikit_learn.py
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Expand Up @@ -224,7 +224,12 @@ def predict(self, x, **kwargs):
Class predictions.
"""
kwargs = self.filter_sk_params(Sequential.predict_classes, kwargs)
classes = self.model.predict_classes(x, **kwargs)

proba = self.model.predict(x, **kwargs)
if proba.shape[-1] > 1:
classes = proba.argmax(axis=-1)
else:
classes = (proba > 0.5).astype('int32')
return self.classes_[classes]

def predict_proba(self, x, **kwargs):
Expand All @@ -247,7 +252,8 @@ def predict_proba(self, x, **kwargs):
(instead of `(n_sample, 1)` as in Keras).
"""
kwargs = self.filter_sk_params(Sequential.predict_proba, kwargs)
probs = self.model.predict_proba(x, **kwargs)
# check if the model is sequential or functional
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Comment is no longer relevant?

probs = self.model.predict(x, **kwargs)

# check if binary classification
if probs.shape[1] == 1:
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