How to make multiclass classification using exercise two ?

[maxihidara]

Hi, i am getting confuse, when i try to make multiclass classification using exercise two. How to make multiclass classification using binary classifier. Can i just add class, and feature_matrix in this code ?

def train_classifier(feature_matrix_0, feature_matrix_1, algorithm='SVM'):
"""Train a binary classifier.

Train a binary classifier. First perform Z-score normalization, then
fit

Args:
    feature_matrix_0 (numpy.ndarray): array of shape (n_samples,
        n_features) with examples for Class 0
    feature_matrix_0 (numpy.ndarray): array of shape (n_samples,
        n_features) with examples for Class 1
    alg (str): Type of classifer to use. Currently only SVM is
        supported.

Returns:
    (sklearn object): trained classifier (scikit object)
    (numpy.ndarray): normalization mean
    (numpy.ndarray): normalization standard deviation
"""
# Create vector Y (class labels)
class0 = np.zeros((feature_matrix_0.shape[0], 1))
class1 = np.ones((feature_matrix_1.shape[0], 1))

# Concatenate feature matrices and their respective labels
y = np.concatenate((class0, class1), axis=0)
features_all = np.concatenate((feature_matrix_0, feature_matrix_1),
                              axis=0)