public class REPTree extends Classifier implements OptionHandler, WeightedInstancesHandler, Drawable, AdditionalMeasureProducer, Sourcable, Randomizable
-M <minimum number of instances> Set minimum number of instances per leaf (default 2).
-V <minimum variance for split> Set minimum numeric class variance proportion of train variance for split (default 1e-3).
-N <number of folds> Number of folds for reduced error pruning (default 3).
-S <seed> Seed for random data shuffling (default 1).
-P No pruning.
-L Maximum tree depth (default -1, no maximum)
BayesNet, Newick, NOT_DRAWABLE, TREE
Constructor and Description |
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REPTree() |
Modifier and Type | Method and Description |
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void |
buildClassifier(Instances data)
Builds classifier.
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double[] |
distributionForInstance(Instance instance)
Computes class distribution of an instance using the tree.
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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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int |
getMaxDepth()
Get the value of MaxDepth.
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double |
getMeasure(String additionalMeasureName)
Returns the value of the named measure.
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double |
getMinNum()
Get the value of MinNum.
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double |
getMinVarianceProp()
Get the value of MinVarianceProp.
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boolean |
getNoPruning()
Get the value of NoPruning.
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int |
getNumFolds()
Get the value of NumFolds.
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String[] |
getOptions()
Gets options from this classifier.
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String |
getRevision()
Returns the revision string.
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int |
getSeed()
Get the value of Seed.
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String |
globalInfo()
Returns a string describing classifier
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String |
graph()
Outputs the decision tree as a graph
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int |
graphType()
Returns the type of graph this classifier
represents.
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Enumeration |
listOptions()
Lists the command-line options for this classifier.
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static void |
main(String[] argv)
Main method for this class.
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String |
maxDepthTipText()
Returns the tip text for this property
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String |
minNumTipText()
Returns the tip text for this property
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String |
minVariancePropTipText()
Returns the tip text for this property
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String |
noPruningTipText()
Returns the tip text for this property
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String |
numFoldsTipText()
Returns the tip text for this property
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int |
numNodes()
Computes size of the tree.
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String |
seedTipText()
Returns the tip text for this property
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void |
setMaxDepth(int newMaxDepth)
Set the value of MaxDepth.
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void |
setMinNum(double newMinNum)
Set the value of MinNum.
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void |
setMinVarianceProp(double newMinVarianceProp)
Set the value of MinVarianceProp.
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void |
setNoPruning(boolean newNoPruning)
Set the value of NoPruning.
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void |
setNumFolds(int newNumFolds)
Set the value of NumFolds.
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void |
setOptions(String[] options)
Parses a given list of options.
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void |
setSeed(int newSeed)
Set the value of Seed.
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String |
toSource(String className)
Returns the tree as if-then statements.
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String |
toString()
Outputs the decision tree.
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classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
public String globalInfo()
public String noPruningTipText()
public boolean getNoPruning()
public void setNoPruning(boolean newNoPruning)
newNoPruning
- Value to assign to NoPruning.public String minNumTipText()
public double getMinNum()
public void setMinNum(double newMinNum)
newMinNum
- Value to assign to MinNum.public String minVariancePropTipText()
public double getMinVarianceProp()
public void setMinVarianceProp(double newMinVarianceProp)
newMinVarianceProp
- Value to assign to MinVarianceProp.public String seedTipText()
public int getSeed()
getSeed
in interface Randomizable
public void setSeed(int newSeed)
setSeed
in interface Randomizable
newSeed
- Value to assign to Seed.public String numFoldsTipText()
public int getNumFolds()
public void setNumFolds(int newNumFolds)
newNumFolds
- Value to assign to NumFolds.public String maxDepthTipText()
public int getMaxDepth()
public void setMaxDepth(int newMaxDepth)
newMaxDepth
- Value to assign to MaxDepth.public Enumeration listOptions()
listOptions
in interface OptionHandler
listOptions
in class Classifier
public String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class Classifier
public void setOptions(String[] options) throws Exception
-M <minimum number of instances> Set minimum number of instances per leaf (default 2).
-V <minimum variance for split> Set minimum numeric class variance proportion of train variance for split (default 1e-3).
-N <number of folds> Number of folds for reduced error pruning (default 3).
-S <seed> Seed for random data shuffling (default 1).
-P No pruning.
-L Maximum tree depth (default -1, no maximum)
setOptions
in interface OptionHandler
setOptions
in class Classifier
options
- the list of options as an array of stringsException
- if an option is not supportedpublic int numNodes()
public Enumeration enumerateMeasures()
enumerateMeasures
in interface AdditionalMeasureProducer
public double getMeasure(String additionalMeasureName)
getMeasure
in interface AdditionalMeasureProducer
additionalMeasureName
- the name of the measure to query for its valueIllegalArgumentException
- if the named measure is not supportedpublic Capabilities getCapabilities()
getCapabilities
in interface CapabilitiesHandler
getCapabilities
in class Classifier
Capabilities
public void buildClassifier(Instances data) throws Exception
buildClassifier
in class Classifier
data
- the data to train withException
- if building failspublic double[] distributionForInstance(Instance instance) throws Exception
distributionForInstance
in class Classifier
instance
- the instance to compute the distribution forException
- if computation failspublic String toSource(String className) throws Exception
public int graphType()
public String toString()
public String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class Classifier
public static void main(String[] argv)
argv
- the commandline optionsCopyright © 2019 University of Waikato, Hamilton, NZ. All rights reserved.