TSK models that are using the hybrid method for training. For the task 1 use Airfoil Self-Noise Data Set. For the task 2 use Superconductivty Data Set
- Use grid partition
- Change the output function to constant
- Use 2 membership function
- Use gbellmf as membership function type
- Train the TSK model with hybrid method
- Evaluate the model
- R2
- RMSE
- NMSE
- NDEI
- Use grid partition
- Change the output function to constant
- Use 3 membership function
- Use gbellmf as membership function type
- Train the TSK model with hybrid method
- Evaluate the model
- R2
- RMSE
- NMSE
- NDEI
- Use grid partition
- Change the output function to linear
- Use 2 membership function
- Use gbellmf as membership function type
- Train the TSK model with hybrid method
- Evaluate the model
- R2
- RMSE
- NMSE
- NDEI
- Use grid partition
- Change the output function to linear
- Use 3 membership function
- Use gbellmf as membership function type
- Train the TSK model with hybrid method
- Evaluate the model
- R2
- RMSE
- NMSE
- NDEI
- Use Subtractive Clustering
- Create a grid search for the best number of features and values of radii
- Use relieff for feature selection
- Compare metrics between models to find the best parameters