GaussianProcesses
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 |