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Package

weka.classifiers.functions

Synopsis

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

Options

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.

Capabilities

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

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