weka.classifiers.pmml.consumer

Class TreeModel

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.pmml.consumer.PMMLClassifier

weka.classifiers.pmml.consumer.TreeModel

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Classifier, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, Drawable, OptionHandler, PMMLModel, RevisionHandler

public class TreeModel
extends PMMLClassifier
implements Drawable

Class implementing import of PMML TreeModel. Can be used as a Weka classifier for prediction (buildClassifier() raises and Exception).

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected weka.classifiers.pmml.consumer.TreeModel.MiningFunction	m_functionType The mining function
protected double	m_missingValuePenalty The missing value penalty (if defined).
protected weka.classifiers.pmml.consumer.TreeModel.MissingValueStrategy	m_missingValueStrategy The missing value strategy
protected weka.classifiers.pmml.consumer.TreeModel.NoTrueChildStrategy	m_noTrueChildStrategy The no true child strategy to use
protected weka.classifiers.pmml.consumer.TreeModel.TreeNode	m_root The root of the tree
protected weka.classifiers.pmml.consumer.TreeModel.SplitCharacteristic	m_splitCharacteristic The splitting type

Fields inherited from class weka.classifiers.pmml.consumer.PMMLClassifier

m_creatorApplication, m_dataDictionary, m_fieldsMap, m_initialized, m_log, m_miningSchema, m_pmmlVersion

Fields inherited from class weka.classifiers.AbstractClassifier

BATCH_SIZE_DEFAULT, m_BatchSize, m_Debug, m_DoNotCheckCapabilities, m_numDecimalPlaces, NUM_DECIMAL_PLACES_DEFAULT

Fields inherited from interface weka.core.Drawable

BayesNet, Newick, NOT_DRAWABLE, TREE

Constructor Summary

Constructors

Constructor and Description
TreeModel(org.w3c.dom.Element model, Instances dataDictionary, MiningSchema miningSchema)

Method Summary

Modifier and Type	Method and Description
double[]	distributionForInstance(Instance inst) Classifies the given test instance.
java.lang.String	getRevision() Returns the revision string.
java.lang.String	graph() Returns a string that describes a graph representing the object.
int	graphType() Returns the type of graph representing the object.
java.lang.String	toString()

Methods inherited from class weka.classifiers.pmml.consumer.PMMLClassifier

buildClassifier, done, getCreatorApplication, getDataDictionary, getFieldsMappingString, getLog, getMiningSchema, getPMMLVersion, mapToMiningSchema, setCreatorApplication, setLog, setPMMLVersion

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getCapabilities, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, getOptions, implementsMoreEfficientBatchPrediction, listOptions, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces, setOptions

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

m_functionType

protected weka.classifiers.pmml.consumer.TreeModel.MiningFunction m_functionType

The mining function

m_missingValueStrategy

protected weka.classifiers.pmml.consumer.TreeModel.MissingValueStrategy m_missingValueStrategy

The missing value strategy

m_missingValuePenalty

protected double m_missingValuePenalty

The missing value penalty (if defined). We don't actually make use of this since we always return full probability distributions.

m_noTrueChildStrategy

protected weka.classifiers.pmml.consumer.TreeModel.NoTrueChildStrategy m_noTrueChildStrategy

The no true child strategy to use

m_splitCharacteristic

protected weka.classifiers.pmml.consumer.TreeModel.SplitCharacteristic m_splitCharacteristic

The splitting type

m_root

protected weka.classifiers.pmml.consumer.TreeModel.TreeNode m_root

The root of the tree

Constructor Detail

TreeModel

public TreeModel(org.w3c.dom.Element model,
                 Instances dataDictionary,
                 MiningSchema miningSchema)
          throws java.lang.Exception

Throws:

java.lang.Exception

Method Detail

distributionForInstance

public double[] distributionForInstance(Instance inst)
                                 throws java.lang.Exception

Classifies the given test instance. The instance has to belong to a dataset when it's being classified.

Specified by:

distributionForInstance in interface Classifier

Overrides:

distributionForInstance in class AbstractClassifier

Parameters:

inst - the instance to be classified

Returns:

the predicted most likely class for the instance or Utils.missingValue() if no prediction is made

Throws:

java.lang.Exception - if an error occurred during the prediction

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

graph

public java.lang.String graph()
                       throws java.lang.Exception

Description copied from interface: Drawable

Returns a string that describes a graph representing the object. The string should be in XMLBIF ver. 0.3 format if the graph is a BayesNet, otherwise it should be in dotty format.

Specified by:

graph in interface Drawable

Returns:

the graph described by a string

Throws:

java.lang.Exception - if the graph can't be computed

getRevision

public java.lang.String getRevision()

Description copied from class: AbstractClassifier

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class AbstractClassifier

Returns:

the revision

graphType

public int graphType()

Description copied from interface: Drawable

Returns the type of graph representing the object.

Specified by:

graphType in interface Drawable

Returns:

the type of graph representing the object