8442ee853b9cb7813689d9dfb381af0976bc5825,pyglmnet/pyglmnet.py,GLM,predict,#GLM#Any#,679

Before Change

            if isinstance(self.fit_, dict):
                yhat = yhat.argmax(axis=1)
            else:
                yhat = yhat.argmax(axis=2)

        return yhat

    def predict_proba(self, X):

After Change

            yhat = _lmb(self.distr, self.fit_["beta0"],
                        self.fit_["beta"], X, self.eta)
            if self.distr == "binomial":
                yhat = (yhat > 0.5).astype(int)
        yhat = np.asarray(yhat)
        return yhat

    def predict_proba(self, X):

Instances