Hyperparameter Random Search
This is the first hyperparameter search for the CNN-GRU hybrid neural network to forecast the energy load of residential areas using multiple features, incl. the load, sunshine minutes, dry temperature, daylengths, weekends, weekdays, and months.
Created on May 3|Last edited on May 3
Comment
Section 1 - Validation Loss
A parallel coordinate plot displaying the parameters used in the runs for the four lowest (<= 0.1444) validation losses is shown below. Further, the parameter importance is shown together with the correlation between the parameter and the lowest validation loss.
Run set
4
Training and Validation Performance Metrics
Run set
4
Section 2 - Validation MAE + MAPE
This section provides an overview of the parameters used for achieving the lowest MAE and MAPE during the runs. Below four runs, identical to the four in section 1, are shown together with their respective parameter importances.
Run set
4
Section 3 - Which NOT to use
The three worst runs are shown below with their selected parameters.
Run set
12
Add a comment