public class LADTree extends Classifier implements Drawable, AdditionalMeasureProducer, TechnicalInformationHandler
 @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
BayesNet, Newick, NOT_DRAWABLE, TREE| Constructor and Description | 
|---|
| LADTree() | 
| Modifier and Type | Method and Description | 
|---|---|
| void | buildClassifier(Instances instances)Builds a classifier for a set of instances. | 
| double[] | distributionForInstance(Instance instance)Returns the class probability distribution for an instance. | 
| void | done() | 
| java.util.Enumeration | enumerateMeasures()Returns an enumeration of the additional measure names. | 
| Capabilities | getCapabilities()Returns default capabilities of the classifier. | 
| double | getMeasure(java.lang.String additionalMeasureName)Returns the value of the named measure. | 
| int | getNumOfBoostingIterations()Gets the number of boosting iterations. | 
| java.lang.String[] | getOptions()Gets the current settings of ADTree. | 
| java.lang.String | getRevision()Returns the revision string. | 
| 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. | 
| java.lang.String | globalInfo()Returns a string describing classifier | 
| java.lang.String | graph()Returns graph describing the tree. | 
| int | graphType()Returns the type of graph this classifier
  represents. | 
| void | initClassifier(Instances instances)Sets up the tree ready to be trained. | 
| java.lang.String | legend()Returns the legend of the tree, describing how results are to be interpreted. | 
| java.util.Enumeration | listOptions()Returns an enumeration describing the available options. | 
| static void | main(java.lang.String[] argv)Main method for testing this class. | 
| double | measureExamplesCounted()Returns the number of examples "counted". | 
| double | measureNodesExpanded()Returns the number of nodes expanded. | 
| double | measureNumLeaves()Calls measure function for leaf size. | 
| double | measureNumPredictionLeaves()Calls measure function for leaf size. | 
| double | measureTreeSize()Calls measure function for tree size. | 
| void | merge(LADTree mergeWith)Merges two trees together. | 
| void | next(int iteration) | 
| java.lang.String | numOfBoostingIterationsTipText() | 
| int | predictiveError(Instances test) | 
| void | setNumOfBoostingIterations(int b)Sets the number of boosting iterations. | 
| void | setOptions(java.lang.String[] options)Parses a given list of options. | 
| java.lang.String | toString()Returns a description of the classifier. | 
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebugpublic java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation in interface TechnicalInformationHandlerpublic void initClassifier(Instances instances) throws java.lang.Exception
instances - the instances to train the tree withjava.lang.Exception - if training data is unsuitablepublic void next(int iteration)
          throws java.lang.Exception
java.lang.Exceptionpublic void done()
          throws java.lang.Exception
java.lang.Exceptionpublic double[] distributionForInstance(Instance instance)
distributionForInstance in class Classifierinstance - the instance to be classifiedpublic java.lang.String toString()
toString in class java.lang.Objectpublic java.lang.String graph()
                       throws java.lang.Exception
public java.lang.String legend()
public java.lang.String numOfBoostingIterationsTipText()
public int getNumOfBoostingIterations()
public void setNumOfBoostingIterations(int b)
b - the number of boosting iterations to usepublic java.util.Enumeration listOptions()
listOptions in interface OptionHandlerlistOptions in class Classifierpublic void setOptions(java.lang.String[] options)
                throws java.lang.Exception
 -B num 
 Set the number of boosting iterations
 (default 10) 
setOptions in interface OptionHandlersetOptions in class Classifieroptions - the list of options as an array of stringsjava.lang.Exception - if an option is not supportedpublic java.lang.String[] getOptions()
getOptions in interface OptionHandlergetOptions in class Classifierpublic double measureTreeSize()
public double measureNumLeaves()
public double measureNumPredictionLeaves()
public double measureNodesExpanded()
public double measureExamplesCounted()
public java.util.Enumeration enumerateMeasures()
enumerateMeasures in interface AdditionalMeasureProducerpublic double getMeasure(java.lang.String additionalMeasureName)
getMeasure in interface AdditionalMeasureProducermeasureName - the name of the measure to query for its valuejava.lang.IllegalArgumentException - if the named measure is not supportedpublic void buildClassifier(Instances instances) throws java.lang.Exception
buildClassifier in class Classifierinstances - the instances to train the classifier withjava.lang.Exception - if something goes wrongpublic int predictiveError(Instances test)
public void merge(LADTree mergeWith) throws java.lang.Exception
mergeWith - the tree to merge withjava.lang.Exception - if merge could not be performedpublic int graphType()
public java.lang.String getRevision()
getRevision in interface RevisionHandlergetRevision in class Classifierpublic Capabilities getCapabilities()
getCapabilities in interface CapabilitiesHandlergetCapabilities in class ClassifierCapabilitiespublic static void main(java.lang.String[] argv)
argv - the options