Package weka.classifiers.trees.m5
Class PreConstructedLinearModel
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.trees.m5.PreConstructedLinearModel
- All Implemented Interfaces:
Serializable
,Cloneable
,CapabilitiesHandler
,OptionHandler
,RevisionHandler
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: 1.6 $
- Author:
- Mark Hall (mhall@cs.waikato.ac.nz)
- See Also:
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionvoid
buildClassifier
(Instances instances) Builds the classifier.double
classifyInstance
(Instance inst) Predicts the class of the supplied instance using the linear model.double[]
Return the array of coefficientsReturns the revision string.double
Return the interceptint
Return the number of parameters (coefficients) in the linear modeltoString()
Returns a textual description of this linear modelMethods inherited from class weka.classifiers.Classifier
debugTipText, distributionForInstance, forName, getCapabilities, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions
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Constructor Details
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PreConstructedLinearModel
public PreConstructedLinearModel(double[] coeffs, double intercept) Constructor- Parameters:
coeffs
- an array of coefficientsintercept
- the intercept
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Method Details
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buildClassifier
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 classClassifier
- Parameters:
instances
- anInstances
value- Throws:
Exception
- if an error occurs
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classifyInstance
Predicts the class of the supplied instance using the linear model.- Overrides:
classifyInstance
in classClassifier
- Parameters:
inst
- the instance to make a prediction for- Returns:
- the prediction
- Throws:
Exception
- if an error occurs
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numParameters
public int numParameters()Return the number of parameters (coefficients) in the linear model- Returns:
- the number of parameters
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coefficients
public double[] coefficients()Return the array of coefficients- Returns:
- the coefficients
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intercept
public double intercept()Return the intercept- Returns:
- the intercept
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toString
Returns a textual description of this linear model -
getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classClassifier
- Returns:
- the revision
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