Keras LSTM 模型构建、训练、预测和评估

class keras_lstm_model: def create_model(self): ## 创建网络 clear_session()

    ' 整体网络样式为
 
 '
    input_ = Input(
        shape=(1, 5)
    )

    x = LSTM(128,
             return_sequences=True,
             recurrent_dropout=0.2
             )(input_)
    x = LSTM(128,
             recurrent_dropout=0.2
             )(x)
    x = Flatten()(x)
    x = Dense(1)(x)

    self.model = Model(
        inputs=input_,
        outputs=x)  ## 初始化网络

    self.model.compile(
        loss='mean_squared_error',
        optimizer="rmsprop")  ##编译模型
    self.model.summary()  ## 可视化模型打印

def train(self, trainX, trainY):
    return self.model.fit(
        trainX,
        trainY,
        epochs=20,
        batch_size=64
    ) 

def predict(self, testX): return self.model.predict(testX) ## 预测数据

def evaluate(self, testX, testY):
    return self.model.evaluate(testX, testY)  ## 评估模型

def save_model(self, model_file):
    self.model.save(model_file)  ## 保存模型

def load_model(self, model_file):
    self.model = load_model(model_file)  ## 加载模型