com.rapidminer.operator.learner.bayes
Class DistributionModel

java.lang.Object
  com.rapidminer.operator.AbstractIOObject
      com.rapidminer.operator.ResultObjectAdapter
          com.rapidminer.operator.AbstractModel
              com.rapidminer.operator.learner.PredictionModel
                  com.rapidminer.operator.learner.bayes.DistributionModel

All Implemented Interfaces:

IOObject, Model, ResultObject, Saveable, Readable, Reportable, LoggingHandler, java.io.Serializable

Direct Known Subclasses:

KernelDistributionModel, SimpleDistributionModel

public abstract class DistributionModel
extends PredictionModel

DistributionModel is a model for learners which estimate distributions of attribute values from example sets like NaiveBayes. Predictions are calculated as product of the conditional probabilities for all attributes times the class probability. The basic learning concept is to simply count occurances of classes and attribute values. This means no propabilities are calculated during the learning step. This is only done before output. Optionally, this calculation can apply a Laplace correction which means in particular that zero probabilities are avoided which would hide information in distributions of other attributes.

Author:

Tobias Malbrecht

See Also:

Serialized Form

Constructor Summary

DistributionModel(ExampleSet exampleSet)

Method Summary

abstract java.lang.String[]	getAttributeNames()
abstract java.util.Collection<java.lang.Integer>	getClassIndices()
abstract java.lang.String	getClassName(int index)
abstract Distribution	getDistribution(int classIndex, int attributeIndex)
abstract double	getLowerBound(int attributeIndex)
abstract int	getNumberOfAttributes()
abstract int	getNumberOfClasses()
abstract double	getUpperBound(int attributeIndex)
abstract boolean	isDiscrete(int attributeIndex)
abstract ExampleSet	performPrediction(ExampleSet exampleSet, Attribute predictedLabel) Subclasses should iterate through the given example set and set the prediction for each example.

Methods inherited from class com.rapidminer.operator.learner.PredictionModel

apply, checkCompatibility, copyPredictedLabel, createPredictedLabel, getLabel, removePredictedLabel, removePredictedLabel, toString

Methods inherited from class com.rapidminer.operator.AbstractModel

getExtension, getFileDescription, getName, getResultIcon, getTrainingHeader, isUpdatable, setParameter, updateModel

Methods inherited from class com.rapidminer.operator.ResultObjectAdapter

addAction, getActions, getVisualizationComponent, isSavable, log, logError, logNote, logWarning, save, toHTML, toResultString

Methods inherited from class com.rapidminer.operator.AbstractIOObject

copy, getLog, getSource, initWriting, read, setLoggingHandler, setSource, write

Methods inherited from class java.lang.Object

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

Methods inherited from interface com.rapidminer.operator.ResultObject

getActions, getVisualizationComponent, toResultString

Methods inherited from interface com.rapidminer.operator.IOObject

copy, getLog, getSource, setLoggingHandler, setSource, write

Methods inherited from interface com.rapidminer.operator.Saveable

isSavable, save

Constructor Detail

DistributionModel

public DistributionModel(ExampleSet exampleSet)

Method Detail

getAttributeNames

public abstract java.lang.String[] getAttributeNames()

getNumberOfAttributes

public abstract int getNumberOfAttributes()

getLowerBound

public abstract double getLowerBound(int attributeIndex)

getUpperBound

public abstract double getUpperBound(int attributeIndex)

isDiscrete

public abstract boolean isDiscrete(int attributeIndex)

getClassIndices

public abstract java.util.Collection<java.lang.Integer> getClassIndices()

getNumberOfClasses

public abstract int getNumberOfClasses()

getClassName

public abstract java.lang.String getClassName(int index)

getDistribution

public abstract Distribution getDistribution(int classIndex,
                                             int attributeIndex)

performPrediction

public abstract ExampleSet performPrediction(ExampleSet exampleSet,
                                             Attribute predictedLabel)

Description copied from class: PredictionModel

Subclasses should iterate through the given example set and set the prediction for each example. The given predicted label attribute was already be added to the example set and should be used to set the predicted values.

Specified by:

performPrediction in class PredictionModel