使用Keras的问题np_utils.to_categorical [英] Issues using Keras np_utils.to_categorical

问题描述

我正在尝试将一个整数的单热点向量数组转换为一个单热点向量数组，keras可以使用该数组来拟合我的模型.这是代码的相关部分:

I'm trying to make an array of one-hot vector of integers into an array of one-hot vector that keras will be able to use to fit my model. Here's the relevant part of the code:

Y_train = np.hstack(np.asarray(dataframe.output_vector)).reshape(len(dataframe),len(output_cols))
dummy_y = np_utils.to_categorical(Y_train)

下面是显示Y_train和dummy_y实际上是什么的图像.

Below is an image showing what Y_train and dummy_y actually are.

我找不到任何可以帮助我的to_categorical文档.

I couldn't find any documentation for to_categorical that could help me.

谢谢.

推荐答案

np_utils.to_categorical用于将标记数据的数组(从0到nb_classes - 1)转换为一键矢量.

np_utils.to_categorical is used to convert array of labeled data(from 0 to nb_classes - 1) to one-hot vector.

带有示例的官方文档.

In [1]: from keras.utils import np_utils # from keras import utils as np_utils
Using Theano backend.

In [2]: np_utils.to_categorical?
Signature: np_utils.to_categorical(y, num_classes=None)
Docstring:
Convert class vector (integers from 0 to nb_classes) to binary class matrix, for use with categorical_crossentropy.

# Arguments
    y: class vector to be converted into a matrix
    nb_classes: total number of classes

# Returns
    A binary matrix representation of the input.
File:      /usr/local/lib/python3.5/dist-packages/keras/utils/np_utils.py
Type:      function

In [3]: y_train = [1, 0, 3, 4, 5, 0, 2, 1]

In [4]: """ Assuming the labeled dataset has total six classes (0 to 5), y_train is the true label array """

In [5]: np_utils.to_categorical(y_train, num_classes=6)
Out[5]:
array([[ 0.,  1.,  0.,  0.,  0.,  0.],
       [ 1.,  0.,  0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  1.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  1.,  0.],
       [ 0.,  0.,  0.,  0.,  0.,  1.],
       [ 1.,  0.,  0.,  0.,  0.,  0.],
       [ 0.,  0.,  1.,  0.,  0.,  0.],
       [ 0.,  1.,  0.,  0.,  0.,  0.]])

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