af0d98898e2be517096c18335ab10b43b9fd461e,mlxtend/classifier/adaline.py,Adaline,fit,#Adaline#,42

Before Change

        if not len(X.shape) == 2:
            raise ValueError("X must be a 2D array. Try X[:,np.newaxis]")

        if not (np.unique(y) == np.array([-1,  1])).all():
            raise ValueError("Supports only binary class labels -1 and 1")

        if not isinstance(init_weights, np.ndarray):
            self.w_ = np.random.random(1 + X.shape[1])
        else:
            self.w_ = init_weights

After Change

        self.classes_ = np.unique(y)
        if not len(self.classes_) == 2 \
                or not self.classes_[0] in (-1, 0) \
                or not self.classes_[1] == 1:
            raise ValueError("Only supports binary class labels {0, 1} or {-1, 1}.")
        if self.classes_[0] == -1:
            self.thres_ = 0

Instances