5 examples of 'keras.utils.to_categorical' in Python

20
def to_categorical(y, n_class):
21
    return keras.utils.to_categorical(y, n_class)

165
def to_categorical(y, nb_classes):
166
    """Convert class vector to binary class matrix.
167
168
    If the input ``y`` has shape (``nb_samples``,) and contains integers from 0
169
    to ``nb_classes``, the output array will be of dimension
170
    (``nb_samples``, ``nb_classes``).
171
    """
172
173
    y = np.asarray(y, dtype='int32')
174
    y_cat = np.zeros((len(y), nb_classes))
175
    for i in range(len(y)):
176
        y_cat[i, y[i]] = 1.
177
    return y_cat

35
def _to_categorical(x, n_classes):
36
    x = np.array(x, dtype=int).ravel()
37
    n = x.shape[0]
38
    ret = np.zeros((n, n_classes))
39
    ret[np.arange(n), x] = 1
40
    return ret

137
def to_categorical(y, nb_classes=None):
138
    y = np.asarray(y, dtype='int32')
139
140
    if not nb_classes:
141
        nb_classes = np.max(y) + 1
142
143
    Y = np.zeros((len(y), nb_classes))
144
    for i in range(len(y)):
145
        Y[i, y[i]] = 1.
146
147
    return Y

27
def preprocess_dataset_labels(y): # Do not preprocess labels here! => it's done in another script
28
    y = to_categorical(y, num_classes)
29
    return y