愉快的学习就从翻译开始吧_Multi-step Time Series Forecasting_10_Multi-Step LSTM Network_Make LSTM Forecasts

Make LSTM Forecasts/让LSTM预测

The next step is to use the fit LSTM network to make forecasts.

下一步是用拟合的LSTM网络来做预测

A single forecast can be made with the fit LSTM network by calling model.predict(). Again, the data must be formatted into a 3D array with the format [samples, timesteps, features].

通过调用model.predict(),拟合的LSTM网络可以做单个预测,再次,数据必须被格式化为【samples,timesteps,features】的3D数组。

We can wrap this up into a function called forecast_lstm().

我们可以把这打包到一个名为forecast_lstm()的函数。

We can call this function from the make_forecasts() function and update it to accept the model as an argument. The updated version is listed below.

我们可以从make_forecasts()中调用这个函数,并将其更新为接受模型作为参数,下面列出了更新版本

This updated version of the make_forecasts() function can be called as follows:

make_forecasts()函数的更新版本可以调用如下:


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