public class AdditiveRegression extends IteratedSingleClassifierEnhancer implements OptionHandler, AdditionalMeasureProducer, WeightedInstancesHandler, TechnicalInformationHandler
@techreport{Friedman1999, author = {J.H. Friedman}, institution = {Stanford University}, title = {Stochastic Gradient Boosting}, year = {1999}, PS = {http://www-stat.stanford.edu/\~jhf/ftp/stobst.ps} }Valid options are:
-S Specify shrinkage rate. (default = 1.0, ie. no shrinkage)
-I <num> Number of iterations. (default 10)
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.DecisionStump)
Options specific to classifier weka.classifiers.trees.DecisionStump:
-D If set, classifier is run in debug mode and may output additional info to the console
Constructor and Description |
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AdditiveRegression()
Default constructor specifying DecisionStump as the classifier
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AdditiveRegression(Classifier classifier)
Constructor which takes base classifier as argument.
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Modifier and Type | Method and Description |
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void |
buildClassifier(Instances data)
Build the classifier on the supplied data
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double |
classifyInstance(Instance inst)
Classify an instance.
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java.util.Enumeration |
enumerateMeasures()
Returns an enumeration of the additional measure names
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Capabilities |
getCapabilities()
Returns default capabilities of the classifier.
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double |
getMeasure(java.lang.String additionalMeasureName)
Returns the value of the named measure
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java.lang.String[] |
getOptions()
Gets the current settings of the Classifier.
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java.lang.String |
getRevision()
Returns the revision string.
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double |
getShrinkage()
Get the shrinkage rate.
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TechnicalInformation |
getTechnicalInformation()
Returns an instance of a TechnicalInformation object, containing
detailed information about the technical background of this class,
e.g., paper reference or book this class is based on.
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java.lang.String |
globalInfo()
Returns a string describing this attribute evaluator
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java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options.
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static void |
main(java.lang.String[] argv)
Main method for testing this class.
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double |
measureNumIterations()
return the number of iterations (base classifiers) completed
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void |
setOptions(java.lang.String[] options)
Parses a given list of options.
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void |
setShrinkage(double l)
Set the shrinkage parameter
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java.lang.String |
shrinkageTipText()
Returns the tip text for this property
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java.lang.String |
toString()
Returns textual description of the classifier.
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getNumIterations, numIterationsTipText, setNumIterations
classifierTipText, getClassifier, setClassifier
debugTipText, distributionForInstance, forName, getDebug, makeCopies, makeCopy, setDebug
public AdditiveRegression()
public AdditiveRegression(Classifier classifier)
classifier
- the base classifier to usepublic java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
public java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
listOptions
in class IteratedSingleClassifierEnhancer
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-S Specify shrinkage rate. (default = 1.0, ie. no shrinkage)
-I <num> Number of iterations. (default 10)
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.DecisionStump)
Options specific to classifier weka.classifiers.trees.DecisionStump:
-D If set, classifier is run in debug mode and may output additional info to the console
setOptions
in interface OptionHandler
setOptions
in class IteratedSingleClassifierEnhancer
options
- the list of options as an array of stringsjava.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class IteratedSingleClassifierEnhancer
public java.lang.String shrinkageTipText()
public void setShrinkage(double l)
l
- the shrinkage rate.public double getShrinkage()
public Capabilities getCapabilities()
getCapabilities
in interface CapabilitiesHandler
getCapabilities
in class SingleClassifierEnhancer
Capabilities
public void buildClassifier(Instances data) throws java.lang.Exception
buildClassifier
in class IteratedSingleClassifierEnhancer
data
- the training datajava.lang.Exception
- if the classifier could not be built successfullypublic double classifyInstance(Instance inst) throws java.lang.Exception
classifyInstance
in class Classifier
inst
- the instance to predictjava.lang.Exception
- if an error occurspublic java.util.Enumeration enumerateMeasures()
enumerateMeasures
in interface AdditionalMeasureProducer
public double getMeasure(java.lang.String additionalMeasureName)
getMeasure
in interface AdditionalMeasureProducer
additionalMeasureName
- the name of the measure to query for its valuejava.lang.IllegalArgumentException
- if the named measure is not supportedpublic double measureNumIterations()
public java.lang.String toString()
toString
in class java.lang.Object
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class Classifier
public static void main(java.lang.String[] argv)
argv
- should contain the following arguments:
-t training file [-T test file] [-c class index]