Package weka.classifiers.trees.m5
Class Rule
java.lang.Object
weka.classifiers.trees.m5.Rule
- All Implemented Interfaces:
Serializable,RevisionHandler
Generates a single m5 tree or rule
- Version:
- $Revision: 15358 $
- Author:
- Mark Hall
- See Also:
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionvoidbuildClassifier(Instances data) Generates a single rule or m5 model tree.doubleclassifyInstance(Instance instance) Calculates a prediction for an instance using this rule or M5 model treevoidFree up memory consumed by the set of instances not covered by this rule.doubleGet the minimum number of instances to allow at a leaf nodeintGet the number of decimal places.booleanGet the value of regressionTree.Returns the revision string.booleanGet whether or not smoothing has been turned onbooleanGet whether unpruned tree/rules are being generatedbooleanget whether an m5 tree is being used rather than rulesGet the instances not covered by this rulevoidsetMinNumInstances(double minNum) Set the minumum number of instances to allow at a leaf nodevoidsetNumDecimalPlaces(int num) Set the number of decimal places.voidsetRegressionTree(boolean newregressionTree) Set the value of regressionTree.voidsetSmoothing(boolean s) Smooth predictionsvoidsetUnpruned(boolean unpruned) Use unpruned tree/rulesvoidsetUseTree(boolean u) Use an m5 tree rather than generate rulesReturns the top of the tree.toString()Return a description of the m5 tree or rule
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Constructor Details
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Rule
public Rule()Constructor declaration
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Method Details
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buildClassifier
Generates a single rule or m5 model tree.- Parameters:
data- set of instances serving as training data- Throws:
Exception- if the rule has not been generated successfully
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classifyInstance
Calculates a prediction for an instance using this rule or M5 model tree- Parameters:
instance- the instance whos class value is to be predicted- Returns:
- the prediction
- Throws:
Exception- if a prediction can't be made.
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topOfTree
Returns the top of the tree. -
toString
Return a description of the m5 tree or rule -
setUnpruned
public void setUnpruned(boolean unpruned) Use unpruned tree/rules- Parameters:
unpruned- true if unpruned tree/rules are to be generated
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getUnpruned
public boolean getUnpruned()Get whether unpruned tree/rules are being generated- Returns:
- true if unpruned tree/rules are to be generated
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setUseTree
public void setUseTree(boolean u) Use an m5 tree rather than generate rules- Parameters:
u- true if m5 tree is to be used
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getUseTree
public boolean getUseTree()get whether an m5 tree is being used rather than rules- Returns:
- true if an m5 tree is being used.
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setSmoothing
public void setSmoothing(boolean s) Smooth predictions- Parameters:
s- true if smoothing is to be used
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getSmoothing
public boolean getSmoothing()Get whether or not smoothing has been turned on- Returns:
- true if smoothing is being used
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notCoveredInstances
Get the instances not covered by this rule- Returns:
- the instances not covered
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freeNotCoveredInstances
public void freeNotCoveredInstances()Free up memory consumed by the set of instances not covered by this rule. -
getRegressionTree
public boolean getRegressionTree()Get the value of regressionTree.- Returns:
- Value of regressionTree.
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setRegressionTree
public void setRegressionTree(boolean newregressionTree) Set the value of regressionTree.- Parameters:
newregressionTree- Value to assign to regressionTree.
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setMinNumInstances
public void setMinNumInstances(double minNum) Set the minumum number of instances to allow at a leaf node- Parameters:
minNum- the minimum number of instances
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getMinNumInstances
public double getMinNumInstances()Get the minimum number of instances to allow at a leaf node- Returns:
- a
doublevalue
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getNumDecimalPlaces
public int getNumDecimalPlaces()Get the number of decimal places. -
setNumDecimalPlaces
public void setNumDecimalPlaces(int num) Set the number of decimal places. -
getM5RootNode
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getRevision
Returns the revision string.- Specified by:
getRevisionin interfaceRevisionHandler- Returns:
- the revision
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