Package weka.classifiers.trees

Class LADTree

java.lang.Object
weka.classifiers.Classifier
weka.classifiers.trees.LADTree
All Implemented Interfaces:
Serializable, Cloneable, AdditionalMeasureProducer, CapabilitiesHandler, Drawable, OptionHandler, RevisionHandler, TechnicalInformationHandler
public class LADTree extends Classifier implements Drawable, AdditionalMeasureProducer, TechnicalInformationHandler
Class for generating a multi-class alternating decision tree using the LogitBoost strategy. For more info, see

Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Eibe Frank, Mark Hall: Multiclass alternating decision trees. In: ECML, 161-172, 2001.

BibTeX: 

 @inproceedings{Holmes2001,
    author = {Geoffrey Holmes and Bernhard Pfahringer and Richard Kirkby and Eibe Frank and Mark Hall},
    booktitle = {ECML},
    pages = {161-172},
    publisher = {Springer},
    title = {Multiclass alternating decision trees},
    year = {2001}
 }

Valid options are: 

 -B <number of boosting iterations>
  Number of boosting iterations.
  (Default = 10)
 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
Version:
$Revision: 10279 $
Author:
Richard Kirkby
See Also:

  • Constructor Details

    • LADTree

      public LADTree()

  • Method Details

    • 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

    • initClassifier

      public void initClassifier(Instances instances) throws Exception
      Sets up the tree ready to be trained.
      Parameters:
      instances - the instances to train the tree with
      Throws:
      Exception - if training data is unsuitable

    • next

      public void next(int iteration) throws Exception
      Throws:
      Exception

    • done

      public void done() throws Exception
      Throws:
      Exception

    • distributionForInstance

      public double[] distributionForInstance(Instance instance)
      Returns the class probability distribution for an instance.
      Overrides:
      distributionForInstance in class Classifier
      Parameters:
      instance - the instance to be classified
      Returns:
      the distribution the tree generates for the instance

    • toString

      public String toString()
      Returns a description of the classifier.
      Overrides:
      toString in class Object
      Returns:
      a string containing a description of the classifier

    • graph

      public String graph() throws Exception
      Returns graph describing the tree.
      Specified by:
      graph in interface Drawable
      Returns:
      the graph of the tree in dotty format
      Throws:
      Exception - if something goes wrong

    • legend

      public String legend()
      Returns the legend of the tree, describing how results are to be interpreted.
      Returns:
      a string containing the legend of the classifier

    • numOfBoostingIterationsTipText

      public String numOfBoostingIterationsTipText()
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui

    • getNumOfBoostingIterations

      public int getNumOfBoostingIterations()
      Gets the number of boosting iterations.
      Returns:
      the number of boosting iterations

    • setNumOfBoostingIterations

      public void setNumOfBoostingIterations(int b)
      Sets the number of boosting iterations.
      Parameters:
      b - the number of boosting iterations to use

    • listOptions

      public Enumeration listOptions()
      Returns an enumeration describing the available options.
      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:

      -B num
      Set the number of boosting iterations (default 10)

      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 ADTree.
      Specified by:
      getOptions in interface OptionHandler
      Overrides:
      getOptions in class Classifier
      Returns:
      an array of strings suitable for passing to setOptions()

    • measureTreeSize

      public double measureTreeSize()
      Calls measure function for tree size.
      Returns:
      the tree size

    • measureNumLeaves

      public double measureNumLeaves()
      Calls measure function for leaf size.
      Returns:
      the leaf size

    • measureNumPredictionLeaves

      public double measureNumPredictionLeaves()
      Calls measure function for leaf size.
      Returns:
      the leaf size

    • measureNodesExpanded

      public double measureNodesExpanded()
      Returns the number of nodes expanded.
      Returns:
      the number of nodes expanded during search

    • measureExamplesCounted

      public double measureExamplesCounted()
      Returns the number of examples "counted".
      Returns:
      the number of nodes processed during search

    • 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:
      measureName - 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

    • buildClassifier

      public void buildClassifier(Instances instances) throws Exception
      Builds a classifier for a set of instances.
      Specified by:
      buildClassifier in class Classifier
      Parameters:
      instances - the instances to train the classifier with
      Throws:
      Exception - if something goes wrong

    • predictiveError

      public int predictiveError(Instances test)

    • merge

      public void merge(LADTree mergeWith) throws Exception
      Merges two trees together. Modifies the tree being acted on, leaving tree passed as a parameter untouched (cloned). Does not check to see whether training instances are compatible - strange things could occur if they are not.
      Parameters:
      mergeWith - the tree to merge with
      Throws:
      Exception - if merge could not be performed

    • graphType

      public int graphType()
      Returns the type of graph this classifier represents.
      Specified by:
      graphType in interface Drawable
      Returns:
      Drawable.TREE

    • getRevision

      public String getRevision()
      Returns the revision string.
      Specified by:
      getRevision in interface RevisionHandler
      Overrides:
      getRevision in class Classifier
      Returns:
      the revision

    • 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:

    • main

      public static void main(String[] argv)
      Main method for testing this class.
      Parameters:
      argv - the options