小编Jhe*_*ani的帖子

我正在使用基本的 CNN 模型对我的数据进行分类。我的输入数据的维度是 (325, 20, 244,244)。我使用的代码如下：

model = Sequential()
model.add(Dense(2, activation='relu', input_shape=X_train.shape[1:]))
model.add(Dense(2, activation='sigmoid'))

optimizer = ['SGD', 'RMSprop', 'Adagrad', 'Adadelta', 'Adam', 'Adamax', 'Nadam']
epochs = [10, 50, 100]
param_grid = dict(epochs=epochs, optimizer=optimizer)

model.compile(loss='binary_crossentropy', metrics=['accuracy'])
grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring='accuracy', n_jobs=-1, refit='boolean')
grid_result = grid.fit(X_train, Y_train, validation_data=(X_test, Y_test))
print("Best: %f using %s" % (grid_result.best_score_, grid_result.best_params_))

我得到的输出是：

grid_result = grid.fit(X_train, Y_train, validation_data=(X_test, Y_test))

Traceback (most recent call last):

  File "<ipython-input-16-bb553189f3ee>", line 1, in <module>
    grid_result = grid.fit(X_train, Y_train, validation_data=(X_test, Y_test))

  File "C:\Users\Student\Anaconda3\lib\site-packages\sklearn\model_selection\_search.py", …