首页from keras.utils import to_categorical的逆过程

from keras.utils import to_categorical的逆过程

时间: 2024-05-14 17:12:11 浏览: 160

浅谈keras中的keras.utils.to_categorical用法

如下所示： to_categorical(y, num_classes=None, dtype=’float32′) 将整型标签转为onehot。y为int数组，num_classes为标签类别总数，大于max(y)（标签从0开始的）。返回：如果num_classes=None，返回len(y) * [max(y)+1]（维度，m*n表示m行n列矩阵，下同），否则为len(y) * num_classes。说出来显得复杂，请看下面实例。 import keras ohl=keras.utils.to_categorical([1,3]) # ohl=keras.utils.to_cat

The inverse process of `from keras.utils import to_categorical` is `np.argmax()` function from the NumPy library. It converts the one-hot encoded arrays (created using `to_categorical()`) back into numerical labels. Example: ```python import numpy as np from keras.utils import to_categorical # Create numerical labels labels = np.array([0, 1, 2, 1, 0, 2]) # Convert numerical labels to one-hot encoded arrays one_hot_labels = to_categorical(labels) # Convert one-hot encoded arrays back to numerical labels numerical_labels = np.argmax(one_hot_labels, axis=1) print(numerical_labels) # Output: [0 1 2 1 0 2] ```

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