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.
Workflow
Energy Demand Prediction with LSTM - Training
External resources
Used extensions & nodes
Created with KNIME Analytics Platform version 4.2.3
- Go to item
- Go to item
- Go to item
- Go to item
- Go to item
- Go to item
Legal
By using or downloading the workflow, you agree to our terms and conditions.