weka.classifiers.trees.m5

Class PreConstructedLinearModel

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.trees.m5.PreConstructedLinearModel

All Implemented Interfaces:

Serializable, Cloneable, Classifier, CapabilitiesHandler, OptionHandler, RevisionHandler

public class PreConstructedLinearModel
extends AbstractClassifier
implements 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: 8034 $

Author:

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

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
PreConstructedLinearModel(double[] coeffs, double intercept) Constructor

Method Summary

Methods

Modifier and Type	Method and Description
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
String	getRevision() Returns the revision string.
double	intercept() Return the intercept
int	numParameters() Return the number of parameters (coefficients) in the linear model
String	toString() Returns a textual description of this linear model

Methods inherited from class weka.classifiers.AbstractClassifier

debugTipText, distributionForInstance, doNotCheckCapabilitiesTipText, forName, getCapabilities, getDebug, getDoNotCheckCapabilities, getOptions, listOptions, makeCopies, makeCopy, runClassifier, setDebug, setDoNotCheckCapabilities, 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 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 interface Classifier

Parameters:

instances - an Instances value

Throws:

Exception - if an error occurs

classifyInstance

public double classifyInstance(Instance inst)
                        throws Exception

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

Specified by:

classifyInstance in interface Classifier

Overrides:

classifyInstance in class AbstractClassifier

Parameters:

inst - the instance to make a prediction for

Returns:

the prediction

Throws:

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 String toString()

Returns a textual description of this linear model

Overrides:

toString in class Object

Returns:

String containing a description of this linear model

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class AbstractClassifier

Returns:

the revision