weka.classifiers.pmml.consumer

Class Regression

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.pmml.consumer.PMMLClassifier

weka.classifiers.pmml.consumer.Regression

All Implemented Interfaces:

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

public class Regression
extends PMMLClassifier
implements java.io.Serializable

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

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected java.lang.String	m_algorithmName Description of the algorithm
protected weka.classifiers.pmml.consumer.Regression.Normalization	m_normalizationMethod The normalization to use
protected weka.classifiers.pmml.consumer.Regression.RegressionTable[]	m_regressionTables The regression tables for this regression

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

Constructor Summary

Constructors

Constructor and Description
Regression(org.w3c.dom.Element model, Instances dataDictionary, MiningSchema miningSchema) Constructs a new PMML Regression.

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	toString() Return a textual description of this Regression model.

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_algorithmName

protected java.lang.String m_algorithmName

Description of the algorithm

m_regressionTables

protected weka.classifiers.pmml.consumer.Regression.RegressionTable[] m_regressionTables

The regression tables for this regression

m_normalizationMethod

protected weka.classifiers.pmml.consumer.Regression.Normalization m_normalizationMethod

The normalization to use

Constructor Detail

Regression

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

Constructs a new PMML Regression.

Parameters:

model - the Element containing the regression model

dataDictionary - the data dictionary as an Instances object

miningSchema - the mining schema

Throws:

java.lang.Exception - if there is a problem constructing this Regression

Method Detail

toString

public java.lang.String toString()

Return a textual description of this Regression model.

Overrides:

toString in class java.lang.Object

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

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