weka.classifiers.pmml.consumer
Class NeuralNetwork

java.lang.Object
  weka.classifiers.AbstractClassifier
      weka.classifiers.pmml.consumer.PMMLClassifier
          weka.classifiers.pmml.consumer.NeuralNetwork

All Implemented Interfaces:

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

public class NeuralNetwork
extends PMMLClassifier

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

Version:

$Revision 1.0 $

Author:

Mark Hall (mhall{[at]}pentaho{[dot]}com)

See Also:

Serialized Form

Constructor Summary

NeuralNetwork(org.w3c.dom.Element model, Instances dataDictionary, MiningSchema miningSchema)

Method Summary

double[]	distributionForInstance(Instance inst) Classifies the given test instance.
java.lang.String	getRevision() Returns the revision string.
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

classifyInstance, debugTipText, forName, getCapabilities, getDebug, getOptions, listOptions, makeCopies, makeCopy, runClassifier, setDebug, setOptions

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

NeuralNetwork

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

Throws:

java.lang.Exception

Method Detail

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

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