This workflow trains and applies an LSTM network to predict energy demand using lagged values of a time series as input. In the Evaluation and Predictions part the trained model is then used for in-sample and out-of-sample forecasting. The forecasted values are compared to the actual values, and the performance of the forecast is reported via scoring metrics and a line plot.
Used extensions & nodes
Created with KNIME Analytics Platform version 4.2.3
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