keel.Algorithms.Semi_Supervised_Learning.Basic

Class NumericalNaiveBayes

java.lang.Object

keel.Algorithms.Lazy_Learning.LazyAlgorithm

keel.Algorithms.Semi_Supervised_Learning.Basic.NumericalNaiveBayes

public class NumericalNaiveBayes
extends LazyAlgorithm

Numerical Naive Bayes algorithm.

Author:

unknown

Field Summary

Fields inherited from class keel.Algorithms.Lazy_Learning.LazyAlgorithm

confMatrix, initialTime, inputAtt, inputs, modelTime, name, nClasses, nInstances, nulls, outFile, output, prediction, predictions, probabilities, realClass, reference, referenceData, referenceFile, referenceOutput, relation, seed, temp, test, testData, testFile, testOutput, testTime, train, trainConfMatrix, trainData, trainFile, trainingTime, trainOutput, trainPrediction, trainRealClass, trainUnclassified, unclassified

Constructor Summary

Constructors

Constructor and Description
NumericalNaiveBayes(double[][] train, int[] clasesTrain, double[][] test, int[] clasesTest, int clases) Executes the Naive Bayes algorithms with the datasets given.
NumericalNaiveBayes(java.lang.String script) The main method of the class
NumericalNaiveBayes(java.lang.String script, InstanceSet train, InstanceSet test, InstanceSet refer) Executes the Naive Bayes algorithms with the datasets given.

Method Summary

Modifier and Type	Method and Description
protected int	evaluate(double[] example) Evaluates a instance to predict its class.
protected double[]	evaluate2(double[] example) Evaluates a instance to predict its class.
int[]	getPredictions() Returns the predicted classes for each test instance.
double[][]	getProbabilities() Returns the classes probabilities for each test instance.
protected void	readParameters(java.lang.String script) Reads configuration script, to extract the parameter's values.

Methods inherited from class keel.Algorithms.Lazy_Learning.LazyAlgorithm

euclideanDistance, execute, executeReference, manhattanDistance, normalizeReference, normalizeTest, normalizeTrain, printInstance, readConfiguracion, readDataFiles, readDataFiles, readDataFiles, same, setInitialTime

Methods inherited from class java.lang.Object

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

Constructor Detail

NumericalNaiveBayes

public NumericalNaiveBayes(double[][] train,
                           int[] clasesTrain,
                           double[][] test,
                           int[] clasesTest,
                           int clases)

Executes the Naive Bayes algorithms with the datasets given.

Parameters:

train - Training input dataset as arrays.

clasesTrain - Training output dataset as arrays.

test - Test input dataset as arrays.

clasesTest - Test output dataset as arrays.

clases - numnber of classes

NumericalNaiveBayes

public NumericalNaiveBayes(java.lang.String script,
                           InstanceSet train,
                           InstanceSet test,
                           InstanceSet refer)

Executes the Naive Bayes algorithms with the datasets given.

Parameters:

script - Configuration script.

train - Training instances set.

test - Test instances set.

refer - Reference instances set.

NumericalNaiveBayes

public NumericalNaiveBayes(java.lang.String script)

The main method of the class

Parameters:

script - Name of the configuration script

Method Detail

readParameters

protected void readParameters(java.lang.String script)

Reads configuration script, to extract the parameter's values.

Specified by:

readParameters in class LazyAlgorithm

Parameters:

script - Name of the configuration script

evaluate

protected int evaluate(double[] example)

Evaluates a instance to predict its class.

Specified by:

evaluate in class LazyAlgorithm

Parameters:

example - Instance evaluated

Returns:

Class predicted

evaluate2

protected double[] evaluate2(double[] example)

Evaluates a instance to predict its class.

Overrides:

evaluate2 in class LazyAlgorithm

Parameters:

example - Instance evaluated

Returns:

Class predicted

getProbabilities

public double[][] getProbabilities()

Returns the classes probabilities for each test instance.

Returns:

the classes probabilities for each test instance.

getPredictions

public int[] getPredictions()

Returns the predicted classes for each test instance.

Returns:

the predicted classes for each test instance.