1c1b85686b9744f988d05ecdbaca20c198488e7b,lightning/impl/prank.py,PRank,predict,#PRank#,73

Before Change

    def predict(self, X):
        n_samples = X.shape[0]
        pred = np.zeros(X.shape[0], dtype=int)
        for i in xrange(n_samples):
            pred[i] = self._predit(X[i])[0]
        return self.label_encoder_.inverse_transform(pred)

After Change

        n_samples = X.shape[0]
        dot = safe_sparse_dot(X, self.coef_)
        out = np.zeros(n_samples, dtype=np.int32)
        _prank_predict(dot, self.thresholds_, len(self.classes_), out)
        return self.label_encoder_.inverse_transform(out)

Instances