Question

当我将堆叠自动编码器应用为特征选择时出现此错误。

<块引用>

ValueError: logits 和标签必须具有相同的形状 ((None, 20) vs (None, 1))

这是堆叠自动编码器的代码::

import tensorflow

from tensorflow.keras import layers
from tensorflow.keras import activations
from tensorflow.python.keras.layers import Input, Dense
from tensorflow.python.keras.models import Model
from sklearn.preprocessing import MinMaxScaler


def StackedAutoencoder(x_train, x_test, y_train, y_test):
    scalar = MinMaxScaler()
    x_train = scalar.fit_transform(x_train)
    x_test = scalar.fit_transform(x_test)

    input_size = x_train.shape[1]
    hidden_size = 9
    code_size = 3

    input_data = Input(shape=(input_size,))
    hidden_1 = Dense(hidden_size, activation='relu')(input_data)
    code = Dense(code_size, activation='relu')(hidden_1)
    hidden_2 = Dense(hidden_size, activation='relu')(code)
    # decode
    output_data = Dense(input_size, activation='sigmoid')(hidden_2)

    autoencoder = Model(input_data, output_data)
    autoencoder.compile(optimizer='adam', loss='binary_crossentropy')
    autoencoder.fit(x_train, y_train, epochs=30, verbose=0,
                    batch_size=10, validation_data=(x_test, y_test))

    reconstructions = autoencoder.predict(x_test)
    return reconstructions

这是我在 main 中调用算法的代码：

import SAE as FS  # SAE the file of stacked-autoencoder algorithm

print('CurrentFeatureSelection = ', 'Stacked_Autoencoder')
X_train_fs, X_test_fs = FS.StackedAutoencoder(X_train, X_test, y_train, y_test)

我在 Stacked-autoencoder 算法中有这个错误，ValueError: logits and labels must have the same shape ((None, 20) vs (None, 1))

0 个答案: