org.aksw.limes.core.ml.algorithm

Class WombatComplete

java.lang.Object

org.aksw.limes.core.ml.algorithm.ACoreMLAlgorithm

org.aksw.limes.core.ml.algorithm.wombat.AWombat

org.aksw.limes.core.ml.algorithm.WombatComplete

public class WombatComplete
extends AWombat

The complete Wombat algorithm (slow implementation)

Version:

Jul 15, 2016

Author:

Mohamed Sherif (sherif@informatik.uni-leipzig.de)

Field Summary

Fields

Modifier and Type	Field and Description
protected static String	ALGORITHM_NAME
protected ExtendedRefinementNode	bestSolutionNode
protected List<ExtendedClassifier>	classifiers
protected Map<String,AMapping>	diffs
protected int	iterationNr
protected static org.slf4j.Logger	logger
protected int	pruneNodeCount
protected long	pruningTime
protected static boolean	usePruning

Fields inherited from class org.aksw.limes.core.ml.algorithm.wombat.AWombat

isUnsupervised, PARAMETER_ATOMIC_MEASURES, PARAMETER_CHILDREN_PENALTY_WEIGHT, PARAMETER_COMPLEXITY_PENALTY_WEIGHT, PARAMETER_EXECUTION_TIME_IN_MINUTES, PARAMETER_FMEASURE_BETA, PARAMETER_MAX_FITNESS_THRESHOLD, PARAMETER_MAX_ITERATION_TIME_IN_MINUTES, PARAMETER_MAX_ITERATIONS_NUMBER, PARAMETER_MAX_REFINEMENT_TREE_SIZE, PARAMETER_MIN_PROPERTY_COVERAGE, PARAMETER_OVERALL_PENALTY_WEIGHT, PARAMETER_PROPERTY_LEARNING_RATE, PARAMETER_SAVE_MAPPING, PARAMETER_VERBOSE, pseudoFMeasure, sourcePropertiesCoverageMap, sourceSample, sourceUris, sourceVariable, targetPropertiesCoverageMap, targetSample, targetUris, targetVariable, trainingData, wombatParameterNames

Fields inherited from class org.aksw.limes.core.ml.algorithm.ACoreMLAlgorithm

configuration, learningParameters, sourceCache, targetCache

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	WombatComplete() WombatComplete constructor.

Method Summary

Modifier and Type	Method and Description
protected MLResults	activeLearn() Learning method for supervised active core ML algorithm implementations Normally, it is used as a first step to initialize the ML model before going through the active learning process
protected MLResults	activeLearn(AMapping oracleMapping) Learning method for supervised active core ML algorithm implementations.
protected ExtendedRefinementNode	createNode(AMapping mapping, String metricExpr) Create new ExtendedRefinementNode using either real or pseudo-F-Measure
protected ExtendedRefinementNode	createNode(String metricExpr)
ExtendedRefinementNode	findBestSolution()
protected String	getName() Name of the core ML algorithm.
protected AMapping	getNextExamples(int size) Get a set of examples to be added to the mapping.
protected void	init(List<LearningParameter> lp, ACache sourceCache, ACache targetCache) Initialize the core ML algorithm.
protected MLResults	learn(AMapping trainingData) Learning method for supervised core ML algorithm implementations, where the confidence values for each pair in the trainingData determine its truth degree.
protected MLResults	learn(PseudoFMeasure pfm) Learning method for unsupervised core ML algorithm implementations.
protected boolean	supports(MLImplementationType mlType) Check whether the mlType is supported.

Methods inherited from class org.aksw.limes.core.ml.algorithm.wombat.AWombat

fillSampleSourceTargetCaches, findInitialClassifiers, fMeasure, getAtomicMeasures, getBestNode, getBeta, getChildrenPenaltyWeight, getComplexityPenaltyWeight, getExcutionTimeInMinutes, getIterationTimeInMinutes, getMappingOfMetricExpression, getMaxFitnessThreshold, getMaxIterationNumber, getMaxRefinmentTreeSize, getMinPropertyCoverage, getMostPromisingNode, getOverAllPenaltyWeight, getPropertyLearningRate, isUnsupervised, isVerbose, precision, predict, recall, saveMapping, setDefaultParameters

Methods inherited from class org.aksw.limes.core.ml.algorithm.ACoreMLAlgorithm

getConfiguration, getParameter, getParameters, getSourceCache, getTargetCache, setConfiguration, setParameter

Methods inherited from class java.lang.Object

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

Field Detail

ALGORITHM_NAME

protected static final String ALGORITHM_NAME

See Also:

Constant Field Values

logger

protected static org.slf4j.Logger logger

usePruning

protected static boolean usePruning

bestSolutionNode

protected ExtendedRefinementNode bestSolutionNode

classifiers

protected List<ExtendedClassifier> classifiers

iterationNr

protected int iterationNr

diffs

protected Map<String,AMapping> diffs

pruneNodeCount

protected int pruneNodeCount

pruningTime

protected long pruningTime

Constructor Detail

WombatComplete

protected WombatComplete()

WombatComplete constructor.

Method Detail

getName

protected String getName()

Description copied from class: ACoreMLAlgorithm

Name of the core ML algorithm.

Specified by:

getName in class ACoreMLAlgorithm

Returns:

Name of the core ML algorithm.

init

protected void init(List<LearningParameter> lp,
                    ACache sourceCache,
                    ACache targetCache)

Description copied from class: ACoreMLAlgorithm

Initialize the core ML algorithm.

Overrides:

init in class AWombat

Parameters:

lp - learning parameters

sourceCache - the source cache

targetCache - the target cache

learn

protected MLResults learn(AMapping trainingData)

Description copied from class: ACoreMLAlgorithm

Learning method for supervised core ML algorithm implementations, where the confidence values for each pair in the trainingData determine its truth degree.

Specified by:

learn in class ACoreMLAlgorithm

Parameters:

trainingData - used for learning

Returns:

wrap with results

learn

protected MLResults learn(PseudoFMeasure pfm)

Description copied from class: ACoreMLAlgorithm

Learning method for unsupervised core ML algorithm implementations.

Specified by:

learn in class ACoreMLAlgorithm

Parameters:

pfm - pseudo F-measure for unsupervised learning

Returns:

wrap with results

supports

protected boolean supports(MLImplementationType mlType)

Description copied from class: ACoreMLAlgorithm

Check whether the mlType is supported.

Specified by:

supports in class ACoreMLAlgorithm

Parameters:

mlType - machine learning implementation type

Returns:

a boolean value

getNextExamples

protected AMapping getNextExamples(int size)
                            throws UnsupportedMLImplementationException

Description copied from class: ACoreMLAlgorithm

Get a set of examples to be added to the mapping.

Specified by:

getNextExamples in class ACoreMLAlgorithm

Parameters:

size - of the examples

Returns:

the mapping

Throws:

UnsupportedMLImplementationException - Exception

activeLearn

protected MLResults activeLearn(AMapping oracleMapping)
                         throws UnsupportedMLImplementationException

Description copied from class: ACoreMLAlgorithm

Learning method for supervised active core ML algorithm implementations.

Specified by:

activeLearn in class ACoreMLAlgorithm

Parameters:

oracleMapping - mapping from the oracle

Returns:

wrap with results

Throws:

UnsupportedMLImplementationException - if ML implementation is not supported

findBestSolution

public ExtendedRefinementNode findBestSolution()

Returns:

ExtendedRefinementNode containing the best over all solution

activeLearn

protected MLResults activeLearn()
                         throws UnsupportedMLImplementationException

Description copied from class: ACoreMLAlgorithm

Learning method for supervised active core ML algorithm implementations Normally, it is used as a first step to initialize the ML model before going through the active learning process

Specified by:

activeLearn in class ACoreMLAlgorithm

Returns:

wrap with results

Throws:

UnsupportedMLImplementationException - if ML implementation is not supported

createNode

protected ExtendedRefinementNode createNode(String metricExpr)

Parameters:

metricExpr - learning specifications

Returns:

new ExtendedRefinementNode

createNode

protected ExtendedRefinementNode createNode(AMapping mapping,
                                            String metricExpr)

Create new ExtendedRefinementNode using either real or pseudo-F-Measure

Overrides:

createNode in class AWombat

Parameters:

mapping - of the node

metricExpr - learning specifications

Returns:

new ExtendedRefinementNode