Package
weka.classifiers.functions
Synopsis
Implements Gaussian Processes for regression without hyperparameter-tuning. For more information see
David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.
Available in Weka 3.6.x - 3.7.1. Available via the package management system for Weka >= 3.7.2 (gaussianProcesses).
Options
The table below describes the options available for GaussianProcesses.
Option | Description |
|---|---|
debug | If set to true, classifier may output additional info to the console. |
filterType | Determines how/if the data will be transformed. |
kernel | The kernel to use. |
noise | The level of Gaussian Noise (added to the diagonal of the Covariance Matrix). |
Capabilities
The table below describes the capabilites of GaussianProcesses.
Capability | Supported |
|---|---|
Class | Numeric class, Missing class values, Date class |
Attributes | Numeric attributes, Unary attributes, Empty nominal attributes, Binary attributes, Missing values, Nominal attributes |
Min # of instances | 1 |