Java weka.classifiers.functions LinearRegression fields, constructors, methods, implement or subclass

Example usage for Java weka.classifiers.functions LinearRegression fields, constructors, methods, implement or subclass

Introduction

In this page you can find the methods, fields and constructors for weka.classifiers.functions LinearRegression.

The text is from its open source code.

int	SELECTION_M5 Attribute selection method: M5 method
int	SELECTION_NONE Attribute selection method: No attribute selection
int	SELECTION_GREEDY Attribute selection method: Greedy method
Tag[]	TAGS_SELECTION Attribute selection methods

	LinearRegression()

void	buildClassifier(Instances data) Builds a regression model for the given data.
double	classifyInstance(Instance instance) Classifies the given instance using the linear regression function.
double[]	coefficients() Returns the coefficients for this linear model.
void	setAttributeSelectionMethod(SelectedTag method) Sets the method used to select attributes for use in the linear regression.
void	setEliminateColinearAttributes(boolean newEliminateColinearAttributes) Set the value of EliminateColinearAttributes.
void	setOptions(String[] options) Parses a given list of options.
void	setRidge(double newRidge) Set the value of Ridge.
String	toString() Outputs the linear regression model as a string.