FIX: sample_weight='auto' for RidgeClassifier

Nothing great, I came across this bug, while playing with the class_weights option for MultinomialLR. I don't know if there is an issue already for this.

In master

     X = np.array([[-1.0, -1.0], [-1.0, 0], [-.8, -1.0], [1.0, 1.0]])
     y = np.array([1, 1, -1, -1])
     clfa = RidgeClassifier(class_weight='auto')
     clfa.fit(X, y)
     ValueError: object too deep for desired array

This fixes this.