stocks.py 文件源码

def train(X_train, y_train):
    model = Sequential()
    model.add(LSTM(
        lstm_neurons,
        batch_input_shape=(batch_size, X_train.shape[1], X_train.shape[2]),
        stateful=True))
    model.add(Dense(1))
    model.compile(loss='mean_squared_error', optimizer='adam')
    for i in range(epochs):
        print 'batch', i+1
        model.fit(
            X_train,
            y_train,
            epochs=1,
            batch_size=batch_size,
            verbose=2,
            shuffle=False,
            validation_split=0.33)
        model.reset_states()
    return model