Keras框架下的独热编码与解码，让你的数据大变身

这里针对的是处理二维矩阵：

# -*- coding: utf-8 -*-
import numpy as np
from keras.utils import to_categorical


def _OneHot_encode():
    data = np.array([[0, 1, 2],
                     [3, 4, 5],
                     [7, 8, 9],
                     [10, 11, 12]])
    print(data)
    print(data.shape)
    encoded_data = to_categorical(data)
    print(encoded_data.shape)
    print(encoded_data)
    return encoded_data


def _OneHot_decode():
    encoded_data = _OneHot_encode()
    decoded_data = []
    for i in range(encoded_data.shape[0]):
        decoded = np.argmax(encoded_data[i], axis=1)
        decoded_data.append(decoded)
    decoded_data = np.array(decoded_data)
    print(decoded_data.shape)
    return decoded_data


if __name__ == '__main__':
    decoded_data = _OneHot_decode()
    print(decoded_data)

这里编码完是这样的：

[[[1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
  [0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
  [0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]]

 [[0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
  [0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
  [0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0.]]

 [[0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0.]
  [0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0.]
  [0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0.]]

 [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0.]
  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0.]
  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1.]]]

然后解码完又回去了：

[[ 0  1  2]
 [ 3  4  5]
 [ 7  8  9]
 [10 11 12]]