mlpclassification.py 文件源码

def build_model(layers):
    model = Sequential()

    model.add(Dense(layers[1], input_shape=(20,), activation='relu'))
    model.add(Dropout(0.2))  # Dropout overfitting

    # model.add(Dense(layers[2],activation='tanh'))
    # model.add(Dropout(0.2))  # Dropout overfitting

    model.add(Dense(layers[2], activation='relu'))
    model.add(Dropout(0.2))  # Dropout overfitting

    model.add(Dense(output_dim=layers[3]))
    model.add(Activation("softmax"))

    model.summary()

    start = time.time()
    # sgd = SGD(lr=0.5, decay=1e-6, momentum=0.9, nesterov=True)
    # model.compile(loss="mse", optimizer=sgd)
    model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=['accuracy']) # Nadam RMSprop()
    print "Compilation Time : ", time.time() - start
    return model