weka.classifiers.trees.m5
Class PreConstructedLinearModel

java.lang.Object
  |
  +--weka.classifiers.Classifier
        |
        +--weka.classifiers.trees.m5.PreConstructedLinearModel

All Implemented Interfaces:

java.lang.Cloneable, OptionHandler, java.io.Serializable

public class PreConstructedLinearModel

extends Classifier

implements java.io.Serializable

This class encapsulates a linear regression function. It is a classifier but does not learn the function itself, instead it is constructed with coefficients and intercept obtained elsewhere. The buildClassifier method must still be called however as this stores a copy of the training data's header for use in printing the model to the console.

Version:

$Revision: 1.2 $

Author:

Mark Hall (mhall@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

PreConstructedLinearModel(double[] coeffs, double intercept)
Constructor

Method Summary

void	buildClassifier(Instances instances) Builds the classifier.
double	classifyInstance(Instance inst) Predicts the class of the supplied instance using the linear model.
double[]	coefficients() Return the array of coefficients
double	intercept() Return the intercept
int	numParameters() Return the number of parameters (coefficients) in the linear model
java.lang.String	toString() Returns a textual description of this linear model

Methods inherited from class weka.classifiers.Classifier

debugTipText, distributionForInstance, forName, getDebug, getOptions, listOptions, makeCopies, setDebug, setOptions

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

PreConstructedLinearModel

public PreConstructedLinearModel(double[] coeffs,
                                 double intercept)

Constructor

Parameters:

coeffs - an array of coefficients

intercept - the intercept

Method Detail

buildClassifier

public void buildClassifier(Instances instances)
                     throws java.lang.Exception

Builds the classifier. In this case all that is done is that a copy of the training instances header is saved.

Specified by:

buildClassifier in class Classifier

Parameters:

instances - an Instances value

Throws:

java.lang.Exception - if an error occurs

classifyInstance

public double classifyInstance(Instance inst)
                        throws java.lang.Exception

Predicts the class of the supplied instance using the linear model.

Overrides:

classifyInstance in class Classifier

Parameters:

inst - the instance to make a prediction for

Returns:

the prediction

Throws:

java.lang.Exception - if an error occurs

numParameters

public int numParameters()

Return the number of parameters (coefficients) in the linear model

Returns:

the number of parameters

coefficients

public double[] coefficients()

Return the array of coefficients

Returns:

the coefficients

intercept

public double intercept()

Return the intercept

Returns:

the intercept

toString

public java.lang.String toString()

Returns a textual description of this linear model

Overrides:

toString in class java.lang.Object

Returns:

String containing a description of this linear model