J48graft (weka-stable 3.6.14 API)

java.lang.Object
- weka.classifiers.Classifier
- - weka.classifiers.trees.J48graft

All Implemented Interfaces:: Serializable, Cloneable, Sourcable, AdditionalMeasureProducer, CapabilitiesHandler, Drawable, Matchable, OptionHandler, RevisionHandler, Summarizable, TechnicalInformationHandler, WeightedInstancesHandler

public class J48graft
extends Classifier
implements OptionHandler, Drawable, Matchable, Sourcable, WeightedInstancesHandler, Summarizable, AdditionalMeasureProducer, TechnicalInformationHandler

Class for generating a grafted (pruned or unpruned) C4.5 decision tree. For more information, see

Geoff Webb: Decision Tree Grafting From the All-Tests-But-One Partition. In: , San Francisco, CA, 1999.

BibTeX:

 @inproceedings{Webb1999,
    address = {San Francisco, CA},
    author = {Geoff Webb},
    publisher = {Morgan Kaufmann},
    title = {Decision Tree Grafting From the All-Tests-But-One Partition},
    year = {1999}
 }

Valid options are:

 -U
  Use unpruned tree.

 -C <pruning confidence>
  Set confidence threshold for pruning.
  (default 0.25)

 -M <minimum number of instances>
  Set minimum number of instances per leaf.
  (default 2)

 -B
  Use binary splits only.

 -S
  Don't perform subtree raising.

 -L
  Do not clean up after the tree has been built.

 -A
  Laplace smoothing for predicted probabilities.  (note: this option only affects initial tree; grafting process always uses laplace).

 -E
  Relabel when grafting.

Version:: $Revision: 5535 $
Author:: Janice Boughton ([email protected]) (based on J48.java written by Eibe Frank)
See Also:: Serialized Form

Field Summary
- Fields inherited from interface weka.core.Drawable
  BayesNet, Newick, NOT_DRAWABLE, TREE

Constructor Summary

Constructors
Constructor and Description

J48graft()

Constructors
Constructor and Description
`J48graft()`

Method Summary

Methods
Modifier and Type	Method and Description
`String`	`binarySplitsTipText()` Returns the tip text for this property
`void`	`buildClassifier(Instances instances)` Generates the classifier.
`double`	`classifyInstance(Instance instance)` Classifies an instance.
`String`	`confidenceFactorTipText()` Returns the tip text for this property
`double[]`	`distributionForInstance(Instance instance)` Returns class probabilities for an instance.
`Enumeration`	`enumerateMeasures()` Returns an enumeration of the additional measure names
`boolean`	`getBinarySplits()` Get the value of binarySplits.
`Capabilities`	`getCapabilities()` Returns default capabilities of the classifier.
`float`	`getConfidenceFactor()` Get the value of CF.
`double`	`getMeasure(String additionalMeasureName)` Returns the value of the named measure
`int`	`getMinNumObj()` Get the value of minNumObj.
`String[]`	`getOptions()` Gets the current settings of the Classifier.
`boolean`	`getRelabel()` Get the value of relabelling
`String`	`getRevision()` Returns the revision string.
`boolean`	`getSaveInstanceData()` Check whether instance data is to be saved.
`boolean`	`getSubtreeRaising()` Get the value of subtreeRaising.
`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.
`boolean`	`getUnpruned()` Get the value of unpruned.
`boolean`	`getUseLaplace()` Get the value of useLaplace.
`String`	`globalInfo()` Returns a string describing classifier
`String`	`graph()` Returns graph describing the tree.
`int`	`graphType()` Returns the type of graph this classifier represents.
`Enumeration`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(String[] argv)` Main method for testing this class
`double`	`measureNumLeaves()` Returns the number of leaves
`double`	`measureNumRules()` Returns the number of rules (same as number of leaves)
`double`	`measureTreeSize()` Returns the size of the tree
`String`	`minNumObjTipText()` Returns the tip text for this property
`String`	`prefix()` Returns tree in prefix order.
`String`	`relabelTipText()` Returns the tip text for this property
`String`	`saveInstanceDataTipText()` Returns the tip text for this property
`void`	`setBinarySplits(boolean v)` Set the value of binarySplits.
`void`	`setConfidenceFactor(float v)` Set the value of CF.
`void`	`setMinNumObj(int v)` Set the value of minNumObj.
`void`	`setOptions(String[] options)` Parses a given list of options.
`void`	`setRelabel(boolean v)` Set the value of relabelling.
`void`	`setSaveInstanceData(boolean v)` Set whether instance data is to be saved.
`void`	`setSubtreeRaising(boolean v)` Set the value of subtreeRaising.
`void`	`setUnpruned(boolean v)` Set the value of unpruned.
`void`	`setUseLaplace(boolean newuseLaplace)` Set the value of useLaplace.
`String`	`subtreeRaisingTipText()` Returns the tip text for this property
`String`	`toSource(String className)` Returns tree as an if-then statement.
`String`	`toString()` Returns a description of the classifier.
`String`	`toSummaryString()` Returns a superconcise version of the model
`String`	`unprunedTipText()` Returns the tip text for this property
`String`	`useLaplaceTipText()` Returns the tip text for this property

Methods inherited from class weka.classifiers.Classifier
debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - J48graft
```
public J48graft()
```
- Method Detail
  - globalInfo
```
public String globalInfo()
```
    Returns a string describing classifier
    
    Returns:
    a description suitable for displaying in the explorer/experimenter gui
  - getTechnicalInformation
```
public 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.
    
    Specified by:
    
    getTechnicalInformation in interface TechnicalInformationHandler
    
    Returns:
    the technical information about this class
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns default capabilities of the classifier.
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class Classifier
    
    Returns:
    the capabilities of this classifier
    See Also:
    Capabilities
  - buildClassifier
```
public void buildClassifier(Instances instances)
                     throws Exception
```
    Generates the classifier.
    
    Specified by:
    
    buildClassifier in class Classifier
    
    Parameters:
    instances - the data to train the classifier with
    
    Throws:
    
    Exception - if classifier can't be built successfully
  - classifyInstance
```
public double classifyInstance(Instance instance)
                        throws Exception
```
    Classifies an instance.
    
    Overrides:
    
    classifyInstance in class Classifier
    
    Parameters:
    instance - the instance to classify
    
    Returns:
    the classification for the instance
    
    Throws:
    
    Exception - if instance can't be classified successfully
  - distributionForInstance
```
public final double[] distributionForInstance(Instance instance)
                                       throws Exception
```
    Returns class probabilities for an instance.
    
    Overrides:
    
    distributionForInstance in class Classifier
    
    Parameters:
    instance - the instance to calculate the class probabilities for
    
    Returns:
    the class probabilities
    
    Throws:
    
    Exception - if distribution can't be computed successfully
  - graphType
```
public int graphType()
```
    Returns the type of graph this classifier represents.
    
    Specified by:
    
    graphType in interface Drawable
    
    Returns:
    Drawable.TREE
  - graph
```
public String graph()
             throws Exception
```
    Returns graph describing the tree.
    
    Specified by:
    
    graph in interface Drawable
    
    Returns:
    the graph describing the tree
    
    Throws:
    
    Exception - if graph can't be computed
  - prefix
```
public String prefix()
              throws Exception
```
    Returns tree in prefix order.
    
    Specified by:
    
    prefix in interface Matchable
    
    Returns:
    the tree in prefix order
    
    Throws:
    
    Exception - if something goes wrong
  - toSource
```
public String toSource(String className)
                throws Exception
```
    Returns tree as an if-then statement.
    
    Specified by:
    
    toSource in interface Sourcable
    
    Parameters:
    className - the name of the Java class
    
    Returns:
    the tree as a Java if-then type statement
    
    Throws:
    
    Exception - if something goes wrong
  - listOptions
```
public Enumeration listOptions()
```
    Returns an enumeration describing the available options. Valid options are:
    -U
    Use unpruned tree.
    -C confidence
    Set confidence threshold for pruning. (Default: 0.25)
    -M number
    Set minimum number of instances per leaf. (Default: 2)
    -B
    Use binary splits for nominal attributes.
    -S
    Don't perform subtree raising.
    -L
    Do not clean up after the tree has been built. -A
    If set, Laplace smoothing is used for predicted probabilites. (note: this option only affects initial tree; grafting process always uses laplace).
    -E
    Allow relabelling when grafting.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Overrides:
    
    listOptions in class Classifier
    
    Returns:
    an enumeration of all the available options.
  - setOptions
```
public void setOptions(String[] options)
                throws Exception
```
    Parses a given list of options. Valid options are:
```
 -U
  Use unpruned tree.
```
```
 -C <pruning confidence>
  Set confidence threshold for pruning.
  (default 0.25)
```
```
 -M <minimum number of instances>
  Set minimum number of instances per leaf.
  (default 2)
```
```
 -B
  Use binary splits only.
```
```
 -S
  Don't perform subtree raising.
```
```
 -L
  Do not clean up after the tree has been built.
```
```
 -A
  Laplace smoothing for predicted probabilities.  (note: this option only affects initial tree; grafting process always uses laplace).
```
```
 -E
  Relabel when grafting.
```
    Specified by:
    
    setOptions in interface OptionHandler
    
    Overrides:
    
    setOptions in class Classifier
    
    Parameters:
    options - the list of options as an array of strings
    
    Throws:
    
    Exception - if an option is not supported
  - getOptions
```
public String[] getOptions()
```
    Gets the current settings of the Classifier.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Overrides:
    
    getOptions in class Classifier
    
    Returns:
    an array of strings suitable for passing to setOptions
  - useLaplaceTipText
```
public String useLaplaceTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getUseLaplace
```
public boolean getUseLaplace()
```
    Get the value of useLaplace.
    
    Returns:
    Value of useLaplace.
  - setUseLaplace
```
public void setUseLaplace(boolean newuseLaplace)
```
    Set the value of useLaplace.
    
    Parameters:
    newuseLaplace - Value to assign to useLaplace.
  - toString
```
public String toString()
```
    Returns a description of the classifier.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    a description of the classifier
  - toSummaryString
```
public String toSummaryString()
```
    Returns a superconcise version of the model
    
    Specified by:
    
    toSummaryString in interface Summarizable
    
    Returns:
    a summary of the model
  - measureTreeSize
```
public double measureTreeSize()
```
    Returns the size of the tree
    
    Returns:
    the size of the tree
  - measureNumLeaves
```
public double measureNumLeaves()
```
    Returns the number of leaves
    
    Returns:
    the number of leaves
  - measureNumRules
```
public double measureNumRules()
```
    Returns the number of rules (same as number of leaves)
    
    Returns:
    the number of rules
  - enumerateMeasures
```
public Enumeration enumerateMeasures()
```
    Returns an enumeration of the additional measure names
    
    Specified by:
    
    enumerateMeasures in interface AdditionalMeasureProducer
    
    Returns:
    an enumeration of the measure names
  - getMeasure
```
public double getMeasure(String additionalMeasureName)
```
    Returns the value of the named measure
    
    Specified by:
    
    getMeasure in interface AdditionalMeasureProducer
    
    Parameters:
    additionalMeasureName - the name of the measure to query for its value
    
    Returns:
    the value of the named measure
    
    Throws:
    
    IllegalArgumentException - if the named measure is not supported
  - unprunedTipText
```
public String unprunedTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getUnpruned
```
public boolean getUnpruned()
```
    Get the value of unpruned.
    
    Returns:
    Value of unpruned.
  - setUnpruned
```
public void setUnpruned(boolean v)
```
    Set the value of unpruned.
    
    Parameters:
    v - Value to assign to unpruned.
  - relabelTipText
```
public String relabelTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getRelabel
```
public boolean getRelabel()
```
    Get the value of relabelling
    
    Returns:
    Value of relabelling.
  - setRelabel
```
public void setRelabel(boolean v)
```
    Set the value of relabelling.
    
    Parameters:
    v - Value to assign to relabelling flag.
  - confidenceFactorTipText
```
public String confidenceFactorTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getConfidenceFactor
```
public float getConfidenceFactor()
```
    Get the value of CF.
    
    Returns:
    Value of CF.
  - setConfidenceFactor
```
public void setConfidenceFactor(float v)
```
    Set the value of CF.
    
    Parameters:
    v - Value to assign to CF.
  - minNumObjTipText
```
public String minNumObjTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getMinNumObj
```
public int getMinNumObj()
```
    Get the value of minNumObj.
    
    Returns:
    Value of minNumObj.
  - setMinNumObj
```
public void setMinNumObj(int v)
```
    Set the value of minNumObj.
    
    Parameters:
    v - Value to assign to minNumObj.
  - binarySplitsTipText
```
public String binarySplitsTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getBinarySplits
```
public boolean getBinarySplits()
```
    Get the value of binarySplits.
    
    Returns:
    Value of binarySplits.
  - setBinarySplits
```
public void setBinarySplits(boolean v)
```
    Set the value of binarySplits.
    
    Parameters:
    v - Value to assign to binarySplits.
  - subtreeRaisingTipText
```
public String subtreeRaisingTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getSubtreeRaising
```
public boolean getSubtreeRaising()
```
    Get the value of subtreeRaising.
    
    Returns:
    Value of subtreeRaising.
  - setSubtreeRaising
```
public void setSubtreeRaising(boolean v)
```
    Set the value of subtreeRaising.
    
    Parameters:
    v - Value to assign to subtreeRaising.
  - saveInstanceDataTipText
```
public String saveInstanceDataTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getSaveInstanceData
```
public boolean getSaveInstanceData()
```
    Check whether instance data is to be saved.
    
    Returns:
    true if instance data is saved
  - setSaveInstanceData
```
public void setSaveInstanceData(boolean v)
```
    Set whether instance data is to be saved.
    
    Parameters:
    v - true if instance data is to be saved
  - getRevision
```
public String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class Classifier
    
    Returns:
    the revision
  - main
```
public static void main(String[] argv)
```
    Main method for testing this class
    
    Parameters:
    argv - the commandline options

Class J48graft

Field Summary

Fields inherited from interface weka.core.Drawable

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.Classifier

Methods inherited from class java.lang.Object

Constructor Detail

J48graft

Method Detail

globalInfo

getTechnicalInformation

getCapabilities

buildClassifier

classifyInstance

distributionForInstance

graphType

graph

prefix

toSource

listOptions

setOptions

getOptions

useLaplaceTipText

getUseLaplace

setUseLaplace

toString

toSummaryString

measureTreeSize

measureNumLeaves

measureNumRules

enumerateMeasures

getMeasure

unprunedTipText

getUnpruned

setUnpruned

relabelTipText

getRelabel

setRelabel

confidenceFactorTipText

getConfidenceFactor

setConfidenceFactor

minNumObjTipText

getMinNumObj

setMinNumObj

binarySplitsTipText

getBinarySplits

setBinarySplits

subtreeRaisingTipText

getSubtreeRaising

setSubtreeRaising

saveInstanceDataTipText

getSaveInstanceData

setSaveInstanceData

getRevision

main