public abstract class AWombat extends ACoreMLAlgorithm
configuration, learningParameters, sourceCache, targetCache| Modifier | Constructor and Description |
|---|---|
protected |
AWombat() |
| Modifier and Type | Method and Description |
|---|---|
protected double |
computePenalty(Tree<RefinementNode> promesyChild) |
protected RefinementNode |
createNode(AMapping mapping,
String metricExpr)
Create new RefinementNode using either real or pseudo-F-Measure
|
protected RefinementNode |
createNode(String metricExpr) |
AMapping |
executeAtomicMeasure(String sourceProperty,
String targetProperty,
String measure,
double threshold) |
protected void |
fillSampleSourceTargetCaches(AMapping sample) |
protected ExtendedClassifier |
findInitialClassifier(String sourceProperty,
String targetProperty,
String measure)
Computes the atomic classifiers by finding the highest possible F-measure
achievable on a given property pair
|
protected List<ExtendedClassifier> |
findInitialClassifiers() |
protected double |
fMeasure(AMapping predictions)
calculate either a real or a pseudo-F-Measure
|
protected Set<String> |
getAtomicMeasures() |
protected double |
getChildrenPenaltyWeight() |
protected double |
getComplexityPenaltyWeight() |
protected int |
getExcutionTimeInMinutes() |
protected int |
getIterationTimeInMinutes() |
protected AMapping |
getMapingOfMetricExpression(String metricExpression)
Looks first for the input metricExpression in the already constructed tree,
if found the corresponding mapping is returned.
|
protected AMapping |
getMapingOfMetricFromTree(String metricExpression,
Tree<RefinementNode> r) |
protected double |
getMaxFitnessThreshold() |
protected int |
getMaxIterationNumber() |
protected int |
getMaxRefinmentTreeSize() |
protected double |
getMinPropertyCoverage() |
protected Tree<RefinementNode> |
getMostPromisingNode(Tree<RefinementNode> r,
double penaltyWeight)
Get the most promising node as the node with the best F-score
|
protected double |
getOverAllPenaltyWeight() |
protected AMapping |
getPredictions(LinkSpecification ls,
ACache sCache,
ACache tCache)
get mapping from source cache to target cache using metricExpression
|
protected double |
getPropertyLearningRate() |
PseudoFMeasure |
getPseudoFMeasure() |
AMapping |
getTrainingData() |
protected void |
init(List<LearningParameter> lp,
ACache sourceCache,
ACache targetCache)
Initialize the core ML algorithm.
|
boolean |
isUnsupervised() |
protected boolean |
isVerbose() |
protected double |
precision(AMapping predictions)
calculate either a real or a pseudo-Precision
|
protected double |
recall(AMapping predictions)
calculate either a real or a pseudo-Recall
|
void |
setDefaultParameters()
Set default ACoreMLAlgorithm parameters values
|
activeLearn, activeLearn, getConfiguration, getName, getNextExamples, getParameter, getParameters, getSourceCache, getTargetCache, learn, learn, predict, setConfiguration, setParameter, supportspublic static final String PARAMETER_MAX_REFINEMENT_TREE_SIZE
public static final String PARAMETER_MAX_ITERATIONS_NUMBER
public static final String PARAMETER_MAX_ITERATION_TIME_IN_MINUTES
public static final String PARAMETER_EXECUTION_TIME_IN_MINUTES
public static final String PARAMETER_MAX_FITNESS_THRESHOLD
public static final String PARAMETER_MIN_PROPERTY_COVERAGE
public static final String PARAMETER_PROPERTY_LEARNING_RATE
public static final String PARAMETER_OVERALL_PENALTY_WEIGHT
public static final String PARAMETER_CHILDREN_PENALTY_WEIGHT
public static final String PARAMETER_COMPLEXITY_PENALTY_WEIGHT
public static final String PARAMETER_VERBOSE
public static final String PARAMETER_ATOMIC_MEASURES
public static final String PARAMETER_SAVE_MAPPING
protected String sourceVariable
protected String targetVariable
protected PseudoFMeasure pseudoFMeasure
protected AMapping trainingData
protected boolean isUnsupervised
protected Tree<RefinementNode> refinementTreeRoot
protected ACache sourceSample
protected ACache targetSample
protected RefinementNode createNode(AMapping mapping, String metricExpr)
mapping - of the nodemetricExpr - learning specificationsprotected RefinementNode createNode(String metricExpr)
metricExpr - learning specificationspublic AMapping executeAtomicMeasure(String sourceProperty, String targetProperty, String measure, double threshold)
sourceProperty - URItargetProperty - URImeasure - namethreshold - of the LSprotected double fMeasure(AMapping predictions)
predictions - Mappingprotected AMapping getMapingOfMetricExpression(String metricExpression)
metricExpression - learning specificationsprotected AMapping getMapingOfMetricFromTree(String metricExpression, Tree<RefinementNode> r)
metricExpression - learning specificationsr - refinement treeprotected AMapping getPredictions(LinkSpecification ls, ACache sCache, ACache tCache)
ls - learning specificationssCache - source CachetCache - target Cachepublic PseudoFMeasure getPseudoFMeasure()
public AMapping getTrainingData()
protected void init(List<LearningParameter> lp, ACache sourceCache, ACache targetCache)
ACoreMLAlgorithminit in class ACoreMLAlgorithmlp - learning parameterssourceCache - the source cachetargetCache - the target cachepublic boolean isUnsupervised()
protected double precision(AMapping predictions)
predictions - Mappingprotected double recall(AMapping predictions)
predictions - Mappingprotected ExtendedClassifier findInitialClassifier(String sourceProperty, String targetProperty, String measure)
sourceProperty - Property of source to usetargetProperty - Property of target to usemeasure - Measure to be usedpublic void setDefaultParameters()
ACoreMLAlgorithmsetDefaultParameters in class ACoreMLAlgorithmprotected boolean isVerbose()
protected double getOverAllPenaltyWeight()
protected double getChildrenPenaltyWeight()
protected double getComplexityPenaltyWeight()
protected double getMinPropertyCoverage()
protected double getPropertyLearningRate()
protected int getIterationTimeInMinutes()
protected int getExcutionTimeInMinutes()
protected double getMaxFitnessThreshold()
protected int getMaxIterationNumber()
protected int getMaxRefinmentTreeSize()
protected void fillSampleSourceTargetCaches(AMapping sample)
protected Tree<RefinementNode> getMostPromisingNode(Tree<RefinementNode> r, double penaltyWeight)
r - The whole refinement treepenaltyWeight - penalty weightprotected List<ExtendedClassifier> findInitialClassifiers()
protected double computePenalty(Tree<RefinementNode> promesyChild)
promesyChild - promesy childCopyright © 2018. All rights reserved.