'Predict class labels for samples in X.
Parameters
X : {array-like, sparse matrix}, shape = [n_samples, n_features]
Samples.
Returns
C : array, shape = [n_samples]
Predicted class label per sample.'

def predict(self, X):

    scores = self.decision_function(X)
    if (len(scores.shape) == 1):
        indices = (scores > 0).astype(np.int)
    else:
        indices = scores.argmax(axis=1)
    return self.classes_[indices]
