Uses of Class
net.sf.myra.datamining.data.Dataset

Packages that use Dataset
net.sf.myra.datamining   
net.sf.myra.datamining.data   
net.sf.myra.datamining.function   
net.sf.myra.datamining.function.hierarchical   
net.sf.myra.datamining.io   
net.sf.myra.datamining.measure   
net.sf.myra.datamining.measure.hierarchical   
net.sf.myra.datamining.seco   
net.sf.myra.datamining.statistics   
net.sf.myra.datamining.util   
 

Uses of Dataset in net.sf.myra.datamining
 

Methods in net.sf.myra.datamining that return Dataset
 Dataset AbstractObjectiveFunction.getDataset()
           
 

Methods in net.sf.myra.datamining with parameters of type Dataset
 void ClassFrequencyAssignator.assign(ProbabilisticRule rule, Dataset dataset)
          Assigns the class probability array to the specified rule.
 void NoClassAssignator.assign(Rule rule, Dataset dataset)
           
 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)
           
protected  void Main.runTest(Dataset trainingSet, Dataset testSet)
           
protected  void Main.runTrain(Dataset dataset)
           
 void AbstractObjectiveFunction.setDataset(Dataset dataset)
           
 

Constructors in net.sf.myra.datamining with parameters of type Dataset
AbstractObjectiveFunction(Dataset dataset)
          Creates a new AbstractObjectiveFunction instance.
ConfidenceEvaluator(Dataset dataset)
          Default constructor.
UsefulnessHelper(Dataset dataset)
           
 

Uses of Dataset in net.sf.myra.datamining.data
 

Methods in net.sf.myra.datamining.data that return Dataset
 Dataset Dataset.clone()
           
abstract  Dataset Strategy.Type.transform(Node node, Dataset dataset)
           
 Dataset Dataset.withoutDuplicates()
          Returns a new dataset instance without duplicated instances.
 

Methods in net.sf.myra.datamining.data with parameters of type Dataset
 void ContinuousAttribute.domain(Dataset dataset)
          Populates the domain values of this attribute.
abstract  Dataset Strategy.Type.transform(Node node, Dataset dataset)
           
 

Constructors in net.sf.myra.datamining.data with parameters of type Dataset
DistanceContent(Dataset dataset)
          Default constructor.
DistanceHeuristicInformation(Dataset dataset)
          Default constructor.
EntropyContent(Dataset dataset)
           
EntropyHeuristicInformation(Dataset dataset)
          Default constructor.
 

Uses of Dataset in net.sf.myra.datamining.function
 

Constructors in net.sf.myra.datamining.function with parameters of type Dataset
AccuracyFunction(Dataset dataset)
          Default constructor.
ConfidenceCoverageFunction(Dataset dataset)
          Creates a new ConfidenceCoverageFunction instance.
CostMeasureFunction(Dataset dataset)
          Default constructor.
CostMeasureFunction(Dataset dataset, double c)
          Construction with parameter.
ErrorBasedFunction(Dataset dataset)
          Default constructor.
FmeasureFunction(Dataset dataset)
          Default constructor.
FmeasureFunction(Dataset dataset, double beta)
          Construction with parameter.
JaccardFunction(Dataset dataset)
          Creates a new ConfidenceCoverageFunction instance.
KlosgenFunction(Dataset dataset)
          Default constructor.
KlosgenFunction(Dataset dataset, double omega)
          Construction with parameter.
LaplaceFunction(Dataset dataset)
           
MEstimateFunction(Dataset dataset)
          Default constructor.
MEstimateFunction(Dataset dataset, double m)
          Construction with parameter.
RelativeCostMeasureFunction(Dataset dataset)
          Default constructor.
RelativeCostMeasureFunction(Dataset dataset, double cr)
          Construction with parameter.
SensitivitySpecificityFunction(Dataset dataset)
          Creates a new SensitivitySpecificityFunction instance.
 

Uses of Dataset in net.sf.myra.datamining.function.hierarchical
 

Constructors in net.sf.myra.datamining.function.hierarchical with parameters of type Dataset
hFmeasure(Dataset dataset)
          Default constructor.
hJaccard(Dataset dataset)
           
hLocalErrorBasedFunction(Dataset dataset)
           
hLocalJaccard(Dataset dataset)
           
LocalFunction(Dataset dataset)
           
PooledPRCurveFunction(Dataset dataset)
          Default constructor.
VarianceFunction(Dataset dataset)
          Default constructor.
VarianceGainFunction(Dataset dataset)
           
 

Uses of Dataset in net.sf.myra.datamining.io
 

Methods in net.sf.myra.datamining.io that return Dataset
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)
           
 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
abstract  void ProbabilisticExporter.write(Dataset testSet, Model discovered)
           
 void HierarchicalExporter.write(Dataset testSet, Model discovered)
          Writes the predictions to the file.
 void FrequencyExporter.write(Dataset testSet, Model discovered)
           
 void Exporter.write(Dataset testSet, Model discovered)
          Writes the predictions to the file.
 void ConfidenceExporter.write(Dataset testSet, Model discovered)
           
 void ClassFrequencyExporter.write(Dataset testSet, Model discovered)
           
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)
           
 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)
           
 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)
           
protected  void ArffHelper.writeData(Dataset dataset, java.io.PrintWriter writer)
          Writes the ARFF data section.
 

Uses of Dataset in net.sf.myra.datamining.measure
 

Methods in net.sf.myra.datamining.measure with parameters of type Dataset
 Unit<java.lang.Double> MicroAveragedFMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<java.lang.Double> MacroWeightedFMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<java.lang.Double> MacroAveragedFMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<java.lang.Double> InverseMacroWeightedFMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<java.lang.Double> ErrorBasedMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<?> CorrectnessRateMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<java.lang.Double> AccuracyMeasure.evaluate(Dataset dataset, Model model)
           
 

Uses of Dataset in net.sf.myra.datamining.measure.hierarchical
 

Methods in net.sf.myra.datamining.measure.hierarchical with parameters of type Dataset
 Unit<?> WeightedPRCurveMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<?> VarianceMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<?> VarianceGainMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<PRCurveMeasure.CurveArea> PRCurveMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<java.lang.Double> PooledPRCurveMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<?> LevelMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<java.lang.Double> hFmeasureMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<?> AveragedPRCurveMeasure.evaluate(Dataset dataset, Model model)
           
 Unit<java.lang.Double> WeightedPRCurveMeasure.evaluate(Dataset dataset, ProbabilisticRuleModel model)
           
 Unit<PRCurveMeasure.CurveArea> PRCurveMeasure.evaluate(Dataset dataset, ProbabilisticRuleModel model)
           
 Unit<java.lang.Double> PooledPRCurveMeasure.evaluate(Dataset dataset, ProbabilisticRuleModel model)
           
 Unit<java.lang.Double> AveragedPRCurveMeasure.evaluate(Dataset dataset, ProbabilisticRuleModel model)
           
 

Uses of Dataset in net.sf.myra.datamining.seco
 

Methods in net.sf.myra.datamining.seco with parameters of type Dataset
 Model SeCo.run(Dataset dataset)
           
 

Uses of Dataset in net.sf.myra.datamining.statistics
 

Methods in net.sf.myra.datamining.statistics with parameters of type Dataset
 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
 

Methods in net.sf.myra.datamining.util that return Dataset
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
static double RuleParser.averageConfidenceSet(Dataset test, java.util.ArrayList<Rule> rules)
           
static double RuleParser.averageFrequencySet(Dataset test, java.util.ArrayList<Rule> rules)
           
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
ValidationHelper(Dataset dataset)
          Creates a new ValidationHelper.
ValidationHelper(Dataset dataset, int fraction)
          Creates a new ValidationHelper.
 



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