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Uses of Dataset in net.sf.myra.datamining |
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Methods in net.sf.myra.datamining that return Dataset | |
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Dataset |
AbstractObjectiveFunction.getDataset()
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Methods in net.sf.myra.datamining with parameters of type Dataset | |
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void |
ClassFrequencyAssignator.assign(ProbabilisticRule rule,
Dataset dataset)
Assigns the class probability array to the specified rule. |
void |
NoClassAssignator.assign(Rule rule,
Dataset dataset)
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void |
MajorityClassAssignator.assign(Rule rule,
Dataset dataset)
Assigns the rule's class value based on the majority class of the covered examples by the rule. |
void |
FixedClassAssignator.assign(Rule rule,
Dataset dataset)
Assigns the default class value to the rule. |
void |
CoveredClassAssignator.assign(Rule rule,
Dataset dataset)
Assigns all class labels of the covered examples to the rule consequent. |
void |
ClassFrequencyAssignator.assign(Rule rule,
Dataset dataset)
|
void |
ClassAssignator.assign(Rule rule,
Dataset dataset)
Assigns the class value to the specified rule. |
Unit<?> |
Measure.evaluate(Dataset dataset,
Model model)
Evaluates the specified model. |
static java.util.List<Instance> |
Evaluator.findCorrectCases(Rule rule,
Dataset dataset)
Returns the correct covered (the instance class value equals to the specified rule consequent) instances by the specified rule. |
static java.util.List<Instance> |
Evaluator.findCoveredCases(Rule rule,
Dataset dataset)
Returns the covered instances by the specified rule. |
static java.util.Set<java.lang.Integer> |
Evaluator.findIndexedCoveredCases(Rule rule,
Dataset dataset)
Returns a set of indexes of the covered instances by the specified rule. |
static Label |
Evaluator.findMajorityClass(Dataset dataset)
Returns the majority class value among the specified dataset. |
static java.util.List<Instance> |
Evaluator.findNotCoveredCases(Rule rule,
Dataset dataset)
Returns the not covered instances by the specified rule. |
static java.util.List<Instance> |
Evaluator.findPositiveCases(Rule rule,
Dataset dataset)
Returns the positive covered (the instance class value contains the specified rule consequent) instances by the specified rule. |
static DefaultConfidenceFactor |
Evaluator.getConfidenceFactor(Rule rule,
Dataset dataset)
Returns the confidence factor of the specified rule when used to classify the dataset instances. |
static ConfusionMatrix |
Evaluator.getConfusionMatrix(Model model,
Dataset dataset)
Returns the confusion matrix of the specified rule set when used to classify the dataset instances. |
static ConfusionMatrix |
Evaluator.getConfusionMatrix(Model model,
Dataset dataset,
java.lang.String label)
Returns the confusion matrix of the model for the specified class label. |
static ConfusionMatrix |
Evaluator.getConfusionMatrix(Rule rule,
Dataset dataset)
Returns the confusion matrix of the specified rule when used to classify the dataset instances. |
static ConfusionMatrix |
Evaluator.getConfusionMatrix(Rule rule,
Dataset dataset,
java.lang.String label)
Returns the confusion matrix of the rule when used to classify the dataset instances, predicting the specified class label. |
protected void |
Main.print(Dataset dataset)
Prints the dataset information. |
abstract Model |
Classifier.run(Dataset dataset)
Trains the classifier using the specified dataset. |
protected void |
Main.runCrossValidation(Dataset dataset)
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protected void |
Main.runTest(Dataset trainingSet,
Dataset testSet)
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protected void |
Main.runTrain(Dataset dataset)
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void |
AbstractObjectiveFunction.setDataset(Dataset dataset)
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Constructors in net.sf.myra.datamining with parameters of type Dataset | |
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AbstractObjectiveFunction(Dataset dataset)
Creates a new AbstractObjectiveFunction instance. |
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ConfidenceEvaluator(Dataset dataset)
Default constructor. |
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UsefulnessHelper(Dataset dataset)
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Uses of Dataset in net.sf.myra.datamining.data |
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Methods in net.sf.myra.datamining.data that return Dataset | |
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Dataset |
Dataset.clone()
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abstract Dataset |
Strategy.Type.transform(Node node,
Dataset dataset)
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Dataset |
Dataset.withoutDuplicates()
Returns a new dataset instance without duplicated instances. |
Methods in net.sf.myra.datamining.data with parameters of type Dataset | |
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void |
ContinuousAttribute.domain(Dataset dataset)
Populates the domain values of this attribute. |
abstract Dataset |
Strategy.Type.transform(Node node,
Dataset dataset)
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Constructors in net.sf.myra.datamining.data with parameters of type Dataset | |
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DistanceContent(Dataset dataset)
Default constructor. |
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DistanceHeuristicInformation(Dataset dataset)
Default constructor. |
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EntropyContent(Dataset dataset)
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EntropyHeuristicInformation(Dataset dataset)
Default constructor. |
Uses of Dataset in net.sf.myra.datamining.function |
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Constructors in net.sf.myra.datamining.function with parameters of type Dataset | |
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AccuracyFunction(Dataset dataset)
Default constructor. |
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ConfidenceCoverageFunction(Dataset dataset)
Creates a new ConfidenceCoverageFunction instance. |
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CostMeasureFunction(Dataset dataset)
Default constructor. |
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CostMeasureFunction(Dataset dataset,
double c)
Construction with parameter. |
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ErrorBasedFunction(Dataset dataset)
Default constructor. |
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FmeasureFunction(Dataset dataset)
Default constructor. |
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FmeasureFunction(Dataset dataset,
double beta)
Construction with parameter. |
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JaccardFunction(Dataset dataset)
Creates a new ConfidenceCoverageFunction instance. |
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KlosgenFunction(Dataset dataset)
Default constructor. |
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KlosgenFunction(Dataset dataset,
double omega)
Construction with parameter. |
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LaplaceFunction(Dataset dataset)
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MEstimateFunction(Dataset dataset)
Default constructor. |
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MEstimateFunction(Dataset dataset,
double m)
Construction with parameter. |
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RelativeCostMeasureFunction(Dataset dataset)
Default constructor. |
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RelativeCostMeasureFunction(Dataset dataset,
double cr)
Construction with parameter. |
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SensitivitySpecificityFunction(Dataset dataset)
Creates a new SensitivitySpecificityFunction instance. |
Uses of Dataset in net.sf.myra.datamining.function.hierarchical |
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Constructors in net.sf.myra.datamining.function.hierarchical with parameters of type Dataset | |
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hFmeasure(Dataset dataset)
Default constructor. |
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hJaccard(Dataset dataset)
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hLocalErrorBasedFunction(Dataset dataset)
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hLocalJaccard(Dataset dataset)
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LocalFunction(Dataset dataset)
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PooledPRCurveFunction(Dataset dataset)
Default constructor. |
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VarianceFunction(Dataset dataset)
Default constructor. |
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VarianceGainFunction(Dataset dataset)
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Uses of Dataset in net.sf.myra.datamining.io |
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Methods in net.sf.myra.datamining.io that return Dataset | |
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static Dataset |
Helper.open(java.io.File file)
Returns a Dataset instance that represents the data of
the specified file. |
static Dataset |
Helper.open(java.lang.String filename)
Returns a Dataset instance that represents the data of
the specified file. |
abstract Dataset |
Helper.read(java.io.File file)
Returns a Dataset instance that represents the data of
the specified file. |
Dataset |
CN2Helper.read(java.io.File file)
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Dataset |
C45Helper.read(java.io.File file)
|
Dataset |
ArffHelper.read(java.io.File file)
Returns a Dataset instance that represents the data of
the specified ARFF file. |
Dataset |
C45Helper.read(java.io.File directory,
java.lang.String filestem)
|
Dataset |
ExtendedArffHelper.read(java.io.Reader reader)
|
Dataset |
ArffHelper.read(java.io.Reader reader)
Returns a Dataset instance that represents the data of
the specified ARFF file. |
Dataset |
C45Helper.read(java.io.Reader names,
java.io.Reader data)
Returns a Dataset instance that represents the data of
the specified files. |
Dataset |
Helper.read(java.lang.String filename)
Returns a Dataset instance that represents the data of
the specified file. |
Methods in net.sf.myra.datamining.io with parameters of type Dataset | |
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abstract void |
ProbabilisticExporter.write(Dataset testSet,
Model discovered)
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void |
HierarchicalExporter.write(Dataset testSet,
Model discovered)
Writes the predictions to the file. |
void |
FrequencyExporter.write(Dataset testSet,
Model discovered)
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void |
Exporter.write(Dataset testSet,
Model discovered)
Writes the predictions to the file. |
void |
ConfidenceExporter.write(Dataset testSet,
Model discovered)
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void |
ClassFrequencyExporter.write(Dataset testSet,
Model discovered)
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abstract void |
Helper.write(java.io.File directory,
Dataset dataset)
Writes a file representing the specified dataset. |
void |
CN2Helper.write(java.io.File directory,
Dataset dataset)
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void |
C45Helper.write(java.io.File directory,
Dataset dataset)
Writes the specified dataset in the C4.5 input file format (names/data). |
void |
ArffHelper.write(java.io.File directory,
Dataset dataset)
Writes an ARFF file representing the specified dataset. |
abstract void |
Helper.write(java.io.Writer writer,
Dataset dataset)
Writes a file representing the specified dataset. |
void |
CN2Helper.write(java.io.Writer writer,
Dataset dataset)
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void |
C45Helper.write(java.io.Writer writer,
Dataset dataset)
Unsupported operation. |
void |
ArffHelper.write(java.io.Writer writer,
Dataset dataset)
Writes an ARFF file representing the specified dataset. |
protected void |
ExtendedArffHelper.writeData(Dataset dataset,
java.io.PrintWriter writer)
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protected void |
ArffHelper.writeData(Dataset dataset,
java.io.PrintWriter writer)
Writes the ARFF data section. |
Uses of Dataset in net.sf.myra.datamining.measure |
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Methods in net.sf.myra.datamining.measure with parameters of type Dataset | |
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Unit<java.lang.Double> |
MicroAveragedFMeasure.evaluate(Dataset dataset,
Model model)
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Unit<java.lang.Double> |
MacroWeightedFMeasure.evaluate(Dataset dataset,
Model model)
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Unit<java.lang.Double> |
MacroAveragedFMeasure.evaluate(Dataset dataset,
Model model)
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Unit<java.lang.Double> |
InverseMacroWeightedFMeasure.evaluate(Dataset dataset,
Model model)
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Unit<java.lang.Double> |
ErrorBasedMeasure.evaluate(Dataset dataset,
Model model)
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Unit<?> |
CorrectnessRateMeasure.evaluate(Dataset dataset,
Model model)
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Unit<java.lang.Double> |
AccuracyMeasure.evaluate(Dataset dataset,
Model model)
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Uses of Dataset in net.sf.myra.datamining.measure.hierarchical |
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Methods in net.sf.myra.datamining.measure.hierarchical with parameters of type Dataset | |
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Unit<?> |
WeightedPRCurveMeasure.evaluate(Dataset dataset,
Model model)
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Unit<?> |
VarianceMeasure.evaluate(Dataset dataset,
Model model)
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Unit<?> |
VarianceGainMeasure.evaluate(Dataset dataset,
Model model)
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Unit<PRCurveMeasure.CurveArea> |
PRCurveMeasure.evaluate(Dataset dataset,
Model model)
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Unit<java.lang.Double> |
PooledPRCurveMeasure.evaluate(Dataset dataset,
Model model)
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Unit<?> |
LevelMeasure.evaluate(Dataset dataset,
Model model)
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Unit<java.lang.Double> |
hFmeasureMeasure.evaluate(Dataset dataset,
Model model)
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Unit<?> |
AveragedPRCurveMeasure.evaluate(Dataset dataset,
Model model)
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Unit<java.lang.Double> |
WeightedPRCurveMeasure.evaluate(Dataset dataset,
ProbabilisticRuleModel model)
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Unit<PRCurveMeasure.CurveArea> |
PRCurveMeasure.evaluate(Dataset dataset,
ProbabilisticRuleModel model)
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Unit<java.lang.Double> |
PooledPRCurveMeasure.evaluate(Dataset dataset,
ProbabilisticRuleModel model)
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Unit<java.lang.Double> |
AveragedPRCurveMeasure.evaluate(Dataset dataset,
ProbabilisticRuleModel model)
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Uses of Dataset in net.sf.myra.datamining.seco |
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Methods in net.sf.myra.datamining.seco with parameters of type Dataset | |
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Model |
SeCo.run(Dataset dataset)
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Uses of Dataset in net.sf.myra.datamining.statistics |
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Methods in net.sf.myra.datamining.statistics with parameters of type Dataset | |
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Information |
Parser.read(Dataset dataset,
CurveFactory factory,
java.util.Set<java.lang.String> filter)
Parses the specified prediction file. |
Uses of Dataset in net.sf.myra.datamining.util |
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Methods in net.sf.myra.datamining.util that return Dataset | |
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static Dataset |
C45Disc.discretize(Dataset dataset)
Discretizes the specified dataset. |
static Dataset[] |
C45Disc.discretize(Dataset trainingSet,
Dataset testSet)
Discretizes the specified training and test datasets. |
Dataset |
ValidationHelper.getTraining()
|
Dataset |
ValidationHelper.getValidation()
|
Dataset |
SillaARFFConverter.read(java.io.Reader reader)
Returns the dataset instance specified by the reader . |
Dataset |
HoldenARFFConverter.read(java.io.Reader reader)
Returns the dataset instance specified by the reader . |
Dataset |
SillaARFFConverter.read(java.lang.String filename)
Returns the dataset instance specified by the filename . |
Dataset |
HoldenARFFConverter.read(java.lang.String filename)
Returns the dataset instance specified by the filename . |
static Dataset[] |
HierarchicalCrossValidation.split(Dataset dataset,
int folds)
Splits the dataset into folds stratified partitions. |
static Dataset[] |
HierarchicalCrossValidation.split(java.lang.String filename,
int folds)
Splits the dataset into folds stratified partitions. |
Methods in net.sf.myra.datamining.util with parameters of type Dataset | |
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static double |
RuleParser.averageConfidenceSet(Dataset test,
java.util.ArrayList<Rule> rules)
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static double |
RuleParser.averageFrequencySet(Dataset test,
java.util.ArrayList<Rule> rules)
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static double |
RuleParser.averageOrderedList(Dataset test,
java.util.ArrayList<Rule> rules)
|
static Dataset |
C45Disc.discretize(Dataset dataset)
Discretizes the specified dataset. |
static Dataset[] |
C45Disc.discretize(Dataset trainingSet,
Dataset testSet)
Discretizes the specified training and test datasets. |
static void |
HierarchicalCrossValidation.export(Dataset dataset,
java.io.File directory,
Helper helper,
int folds)
Exports the dataset into training, validation and test set. |
static void |
HierarchicalCrossValidation.export(Dataset dataset,
java.io.File directory,
Helper helper,
int folds,
boolean validation)
Exports the dataset into folds partitions. |
static void |
FlatCrossValidation.export(Dataset dataset,
int folds,
java.io.File directory,
FlatCrossValidation.Mode mode,
Helper helper)
Exports the dataset into folds partitions. |
static FlatCrossValidation.Partition[] |
HierarchicalCrossValidation.partition(Dataset dataset,
int folds)
Splits the dataset into folds stratified partitions. |
static Dataset[] |
HierarchicalCrossValidation.split(Dataset dataset,
int folds)
Splits the dataset into folds stratified partitions. |
static FlatCrossValidation.Partition[] |
FlatCrossValidation.split(Dataset dataset,
int folds,
FlatCrossValidation.Mode mode)
Splits the dataset into folds partitions. |
Constructors in net.sf.myra.datamining.util with parameters of type Dataset | |
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ValidationHelper(Dataset dataset)
Creates a new ValidationHelper . |
|
ValidationHelper(Dataset dataset,
int fraction)
Creates a new ValidationHelper . |
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