Module es.upm.fi.cig.multictbnc

Package es.upm.fi.cig.multictbnc.conceptdriftdetection

Class AverageLocalLogLikelihood

java.lang.Object

es.upm.fi.cig.multictbnc.conceptdriftdetection.AverageLocalLogLikelihood

All Implemented Interfaces:

ConceptDriftScore

public class AverageLocalLogLikelihood
extends Object
implements ConceptDriftScore

This class provides a method to compute the average local log-likelihood of each node of a Multi-CTBNC.

Field Summary

Fields

Modifier and Type	Field	Description
protected Map<String,DoubleUnaryOperator>	penalisationFunctionMap	A map that associates penalisation function names with their corresponding mathematical functions.

Constructor Summary

Constructors

Constructor	Description
AverageLocalLogLikelihood(String penalisationFunction)	Constructs an instance of AverageLocalLogLikelihood with a specified penalisation function.

Method Summary

Modifier and Type	Method	Description
double[]	compute(MultiCTBNC<CPTNode,CIMNode> model, Dataset newBatch, List<String> nameVariables)	Compute the score over each node of the provided MultiCTBNC.

Methods inherited from class java.lang.Object

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

Field Details

penalisationFunctionMap

protected Map<String,DoubleUnaryOperator> penalisationFunctionMap

A map that associates penalisation function names with their corresponding mathematical functions.

Constructor Details

AverageLocalLogLikelihood

public AverageLocalLogLikelihood(String penalisationFunction)

Constructs an instance of AverageLocalLogLikelihood with a specified penalisation function.

Parameters:

penalisationFunction - name of the penalisation function

Method Details

compute

public double[] compute(MultiCTBNC<CPTNode,CIMNode> model,
 Dataset newBatch,
 List<String> nameVariables)

Description copied from interface: ConceptDriftScore

Compute the score over each node of the provided MultiCTBNC.

Specified by:

compute in interface ConceptDriftScore

Parameters:

model - MultiCTBNC model to be evaluated for concept drift

newBatch - new data batch that is used to compute the drift score

nameVariables - names of the variables

Returns:

array of doubles representing the drift scores for each node