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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