| Modifier and Type | Method and Description |
|---|---|
static AMapping |
MLPipeline.execute(ACache source,
ACache target,
Configuration configuration,
String mlAlgorithmName,
MLImplementationType mlImplementationType,
List<LearningParameter> learningParameters,
String trainingDataFile,
EvaluatorType pfmType,
int maxIt,
ActiveLearningOracle oracle) |
| Modifier and Type | Field and Description |
|---|---|
Map<EvaluatorType,Double> |
EvaluationRun.qualititativeScores
The qualitative measures scores e.g.
|
Map<EvaluatorType,org.apache.commons.math3.util.Pair<Double,Double>> |
EvaluationRun.qualititativeScoresWithVariance
The qualitative measures scores e.g.
|
| Modifier and Type | Method and Description |
|---|---|
Set<EvaluatorType> |
EvaluationRun.getQualititativeMeasures() |
| Constructor and Description |
|---|
EvaluationRun(String algorithmName,
String datasetName,
Map<EvaluatorType,Double> evaluatorsScores) |
EvaluationRun(String algorithmName,
String datasetName,
Map<EvaluatorType,Double> evaluatorsScores,
RunRecord quantitativeRecord) |
EvaluationRun(String algorithmName,
String implementation,
String datasetName,
Map<EvaluatorType,Double> evaluatorsScores) |
EvaluationRun(String algorithmName,
String implementation,
String datasetName,
Map<EvaluatorType,Double> evaluatorsScores,
int run) |
EvaluationRun(String algorithmName,
String implementation,
String datasetName,
Map<EvaluatorType,Double> evaluatorsScores,
int run,
LinkSpecification learnedLS) |
EvaluationRun(String algorithmName,
String implementation,
String datasetName,
Map<EvaluatorType,Double> evaluatorsScores,
LinkSpecification learnedLS) |
| Modifier and Type | Method and Description |
|---|---|
static EvaluatorType |
EvaluatorType.valueOf(String name)
Returns the enum constant of this type with the specified name.
|
static EvaluatorType[] |
EvaluatorType.values()
Returns an array containing the constants of this enum type, in
the order they are declared.
|
| Modifier and Type | Method and Description |
|---|---|
static IQualitativeMeasure |
EvaluatorFactory.create(EvaluatorType measure) |
| Modifier and Type | Method and Description |
|---|---|
List<EvaluationRun> |
Evaluator.crossValidate(AMLAlgorithm algorithm,
List<LearningParameter> parameter,
Set<TaskData> datasets,
int foldNumber,
Set<EvaluatorType> qlMeasures,
Set<IQuantitativeMeasure> qnMeasures) |
Summary |
Evaluator.crossValidateWithTuningAndStatisticalTest(List<TaskAlgorithm> TaskAlgorithms,
Set<TaskData> datasets,
Set<EvaluatorType> qlMeasures,
int foldNumber) |
List<EvaluationRun> |
Evaluator.evaluate(List<TaskAlgorithm> TaskAlgorithms,
Set<TaskData> datasets,
Set<EvaluatorType> QlMeasures,
Set<IQuantitativeMeasure> QnMeasures) |
| Modifier and Type | Method and Description |
|---|---|
Map<EvaluatorType,Double> |
QualitativeMeasuresEvaluator.evaluate(AMapping predictions,
GoldStandard goldStandard,
Set<EvaluatorType> evaluationMeasures) |
| Modifier and Type | Method and Description |
|---|---|
Map<EvaluatorType,Double> |
QualitativeMeasuresEvaluator.evaluate(AMapping predictions,
GoldStandard goldStandard,
Set<EvaluatorType> evaluationMeasures) |
| Modifier and Type | Field and Description |
|---|---|
protected EvaluatorType |
Configuration.mlPseudoFMeasure |
| Modifier and Type | Method and Description |
|---|---|
EvaluatorType |
Configuration.getMlPseudoFMeasure() |
| Modifier and Type | Method and Description |
|---|---|
void |
Configuration.setMlPseudoFMeasure(EvaluatorType mlPseudoFMeasure) |
| Constructor and Description |
|---|
Configuration(KBInfo sourceInfo,
KBInfo targetInfo,
String metricExpression,
String acceptanceRelation,
String verificationRelation,
double acceptanceThreshold,
String acceptanceFile,
double verificationThreshold,
String verificationFile,
Map<String,String> prefixes,
String outputFormat,
String executionRewriter,
String executionPlanner,
String executionEngine,
int granularity,
String mlAlgorithmName,
List<LearningParameter> mlParameters,
MLImplementationType mlImplementationType,
String mlTrainingDataFile,
EvaluatorType mlPseudoFMeasure,
long maxOpt,
double k) |
Copyright © 2020. All rights reserved.