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

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20def to_categorical(y, n_class):
21 return keras.utils.to_categorical(y, n_class)
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165def 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
35def _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
137def 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
27def 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

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