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Uses of Model in net.sf.myra.datamining |
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Methods in net.sf.myra.datamining that return Model | |
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abstract Model |
Classifier.run(Dataset dataset)
Trains the classifier using the specified dataset. |
Methods in net.sf.myra.datamining with parameters of type Model | |
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void |
Gatherer.add(Model model)
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Unit<?> |
Measure.evaluate(Dataset dataset,
Model model)
Evaluates the specified model. |
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. |
Uses of Model in net.sf.myra.datamining.io |
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Methods in net.sf.myra.datamining.io with parameters of type Model | |
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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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Uses of Model in net.sf.myra.datamining.measure |
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Methods in net.sf.myra.datamining.measure with parameters of type Model | |
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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 Model in net.sf.myra.datamining.measure.hierarchical |
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Methods in net.sf.myra.datamining.measure.hierarchical with parameters of type Model | |
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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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Uses of Model in net.sf.myra.datamining.model |
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Subinterfaces of Model in net.sf.myra.datamining.model | |
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interface |
ProbabilisticModel
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Classes in net.sf.myra.datamining.model that implement Model | |
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class |
AbstractRuleModel
Base class for (flat) rule models. |
class |
ProbabilisticRuleList
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class |
ProbabilisticRuleModel
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class |
ProbabilisticRuleSet
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class |
RuleList
This class represents a rule list model. |
class |
RuleSet
This class represents a rule set model. |
Methods in net.sf.myra.datamining.model with parameters of type Model | |
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void |
AbstractRuleModel.DefaultGatherer.add(Model model)
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Uses of Model in net.sf.myra.datamining.seco |
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Methods in net.sf.myra.datamining.seco that return Model | |
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Model |
SeCo.run(Dataset dataset)
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