LinearRegression

Package

weka.classifiers.functions

Class for using linear regression for prediction. Uses the Akaike criterion for model selection, and is able to deal with weighted instances.

The table below describes the options available for LinearRegression.

Option	Description
attributeSelectionMethod	Set the method used to select attributes for use in the linear regression. Available methods are: no attribute selection, attribute selection using M5's method (step through the attributes removing the one with the smallest standardised coefficient until no improvement is observed in the estimate of the error given by the Akaike information criterion), and a greedy selection using the Akaike information metric.
debug	Outputs debug information to the console.
eliminateColinearAttributes	Eliminate colinear attributes.
ridge	The value of the Ridge parameter.

The table below describes the capabilites of LinearRegression.

Capability	Supported
Class	Missing class values, Numeric class, Date class
Attributes	Numeric attributes, Nominal attributes, Binary attributes, Date attributes, Missing values, Empty nominal attributes, Unary attributes
Min # of instances	1