testh.py 文件源码

def model(X_train, Y_train, X_test, Y_test):
    model = Sequential()
    model.add(Dense({{choice([15, 512, 1024])}},input_dim=8,init='uniform', activation='softplus'))
    model.add(Dropout({{uniform(0, 1)}}))
    model.add(Dense({{choice([256, 512, 1024])}}))
    model.add(Activation({{choice(['relu', 'sigmoid','softplus'])}}))
    model.add(Dropout({{uniform(0, 1)}}))

    model.add(Dense(1, init='uniform', activation='sigmoid'))

    model.compile(loss='mse', metrics=['accuracy'],
                  optimizer={{choice(['rmsprop', 'adam', 'sgd'])}})

    model.fit(X_train, Y_train,
              batch_size={{choice([10, 50, 100])}},
              nb_epoch={{choice([1, 50])}},
              show_accuracy=True,
              verbose=2,
              validation_data=(X_test, Y_test))
    score, acc = model.evaluate(X_test, Y_test, verbose=0)
    print('Test accuracy:', acc)
    return {'loss': -acc, 'status': STATUS_OK, 'model': model}