Implements Gaussian processes for regression without hyperparameter-tuning
To make choosing an appropriate noise level easier, this implementation applies normalization/standardization to the target attribute as well as the other attributes (if normalization/standardizaton is turned on).Missing values are replaced by the global mean/mode.
Nominal attributes are converted to binary ones.Note that kernel caching is turned off if the kernel used implements CachedKernel.
(based on WEKA 3.7)
For further options, click the 'More' - button in the dialog.
All weka dialogs have a panel where you can specify classifier-specific parameters.
- Type: Data Training data
- Type: Weka 3.7 Classifier Trained model