Package org.aksw.limes.core.ml.algorithm.euclid

Class LinearEuclid

java.lang.Object

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

org.aksw.limes.core.ml.algorithm.euclid.LinearEuclid

Direct Known Subclasses:

BooleanEuclid

public class LinearEuclid
extends ACoreMLAlgorithm

Class wraps around EUCLIDs linear classifier to abide LIMES ml interface

Author:

Klaus Lyko (lyko@informatik.uni-leipzig.de)

Field Summary

Fields

Modifier and Type	Field	Description
protected static String	ALGORITHM_NAME
static String	BETA
static String	ITERATIONS_MAX
static String	KAPPA
static String	LEARNING_RATE
protected LinearSelfConfigurator	lsc	The EUCLID implementation
static String	MIN_COVERAGE
static String	MIN_THRESHOLD
static String	STRICT

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

configuration, learningParameters, logger, sourceCache, targetCache

Constructor Summary

Constructors

Constructor	Description
LinearEuclid()

Method Summary

Modifier and Type	Method	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 void	configureEuclid(LinearSelfConfigurator lsc)	To configure EUCLID implementation.
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> learningParameters, ACache sourceCache, ACache targetCache)	Initialize the core ML algorithm.
protected MLResults	learn()	Common learning method for both supervised and unsupervised Euclids.
protected MLResults	learn(PseudoFMeasure pfm)	Learning method for unsupervised core ML algorithm implementations.
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 AMapping	predict(ACache source, ACache target, MLResults mlModel)	Predict/generate links from source to target based on mlModel.
void	setDefaultParameters()	Set default ACoreMLAlgorithm parameters values
protected boolean	supports(MLImplementationType mlType)	Check whether the mlType is supported.

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

STRICT

public static final String STRICT

See Also:

Constant Field Values

ITERATIONS_MAX

public static final String ITERATIONS_MAX

See Also:

Constant Field Values

MIN_THRESHOLD

public static final String MIN_THRESHOLD

See Also:

Constant Field Values

KAPPA

public static final String KAPPA

See Also:

Constant Field Values

BETA

public static final String BETA

See Also:

Constant Field Values

LEARNING_RATE

public static final String LEARNING_RATE

See Also:

Constant Field Values

MIN_COVERAGE

public static final String MIN_COVERAGE

See Also:

Constant Field Values

lsc

protected LinearSelfConfigurator lsc

The EUCLID implementation

Constructor Detail

LinearEuclid

public LinearEuclid()

Method Detail

init

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

Description copied from class: ACoreMLAlgorithm

Initialize the core ML algorithm.

Overrides:

init in class ACoreMLAlgorithm

Parameters:

learningParameters - learning parameters

sourceCache - the source cache

targetCache - the target cache

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.

setDefaultParameters

public void setDefaultParameters()

Description copied from class: ACoreMLAlgorithm

Set default ACoreMLAlgorithm parameters values

Specified by:

setDefaultParameters in class ACoreMLAlgorithm

learn

protected MLResults learn()

Common learning method for both supervised and unsupervised Euclids.

Returns:

MLResults object containing a (equivalent) LS to the Euclids optimization method, a mapping, and eventually further detailed results.

learn

protected MLResults learn(AMapping trainingData)
                   throws UnsupportedMLImplementationException

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

Throws:

UnsupportedMLImplementationException - if ML implementation is not supported

learn

protected MLResults learn(PseudoFMeasure pfm)
                   throws UnsupportedMLImplementationException

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

Throws:

UnsupportedMLImplementationException - if ML implementation is not supported

predict

protected AMapping predict(ACache source,
                           ACache target,
                           MLResults mlModel)

Description copied from class: ACoreMLAlgorithm

Predict/generate links from source to target based on mlModel.

Specified by:

predict in class ACoreMLAlgorithm

Parameters:

source - Cache

target - Cache

mlModel - result of training phase

Returns:

the mapping from source to target

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

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

configureEuclid

protected void configureEuclid(LinearSelfConfigurator lsc)

To configure EUCLID implementation. Checks for new parameters and sets up EUCLID accordingly.