如何添加 Keras 丢弃层?不幸的是,我不知道我必须在哪里添加这一层。我查看了 2 个链接:
- https://keras.io/api/layers/regularization_layers/dropout/
- https://machinelearningmastery.com/dropout-regularization-deep-learning-models-keras/
比如我见过这个
model.add(Dense(60, input_dim=60, activation='relu', kernel_constraint=maxnorm(3)))
model.add(Dropout(0.2))
model.add(Dense(30, activation='relu', kernel_constraint=maxnorm(3)))
model.add(Dropout(0.2))
model.add(Dense(1, activation='sigmoid'))
据我所知,密集层是用循环创建的,所以我不确定如何添加它。
def get_Model(...):
# build dense layer for model
for i in range(1, len(dense_layers)):
layer = Dense(dense_layers[i],
activity_regularizer=l2(reg_layers[i]),
activation='relu',
name='layer%d' % i)
mlp_vector = layer(mlp_vector)
predict_layer = Concatenate()([mf_cat_latent, mlp_vector])
result = Dense(1, activation='sigmoid',
kernel_initializer='lecun_uniform', name='result')
model = Model(inputs=[input_user, input_item], outputs=result(predict_layer))
return model
最佳答案
试试这个:
for i in range(1, len(dense_layers)):
layer = Dense(dense_layers[i],
activity_regularizer=l2(reg_layers[i]),
activation='relu',
name='layer%d' % i)
mlp_vector = layer(mlp_vector)
mlp_vector = Dropout(0.2)(mlp_vector)
在这里查看函数式 API https://keras.io/guides/functional_api/
关于python - 如何添加 keras dropout 层?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/65327655/