b0d52d930aa00b7d0876abffe38e33d8a307b117,keras/wrappers/scikit_learn.py,KerasClassifier,predict_proba,#KerasClassifier#Any#,192

Before Change

                Class probability estimates.
        """
        kwargs = self.filter_sk_params(Sequential.predict_proba, kwargs)
        return self.model.predict_proba(X, **kwargs)

    def score(self, X, y, **kwargs):
        """Returns the mean accuracy on the given test data and labels.

After Change

                 will return "(n_samples, 2)"
        """
        kwargs = self.filter_sk_params(Sequential.predict_proba, kwargs)
        probs = self.model.predict_proba(X, **kwargs)

        // check if binary classification
        if probs.shape[1] == 1:
            // first column is probability of class 0 and second is of class 1

Instances