Package net.sf.myra.datamining

Interface Summary
ClassAssignator This interface represents the mechanism of assigning the predicted class of a rule.
ConfidenceFactor  
Gatherer  
Measure This interface represents a quality measure evaluator of a specified Model instance.
Model This interface represents the knowledge discovered by a classifier.
Unit.DoubleValued Interface to indicate a unit value which can be represented as a double.
 

Class Summary
AbstractObjectiveFunction This class provides a skeletal implementation of the ObjectiveFunction interface.
AbstractPruner This class provides a skeletal implementation of a rule prune procedure based on the LocalSearch interface.
BacktrackPruner This class represents a prune procedure which removes the last term of the rule until the rule quality improves.
ClassFrequencyAssignator  
Classifier This class defines a skeletal implementation of a classifier algorithm.
ConfidenceEvaluator This class represents a daemon action responsible to evaluate the confidence factor of the rules discovered by ants in the current iteration.
ConfusionMatrix This class represents a confusion matrix implementation.
ConvergenceTest This class represents the convergence stop condition.
CoveredClassAssignator  
DefaultConfidenceFactor This class represents the confidence factor measure.
ErrorBasedMetric This class provides the error estimation based on the metric used by C4.5.
ErrorBasedPruner This class implements an error based pruning procedure based on the metric used by C4.5.
Evaluator Utility class to evaluate rules discovered by ants.
FixedClassAssignator This class represents a fixed value (specified in the constructor) class assignator.
HierarchicalPruner  
IterationTest This class represents the iteration stop condition.
Main Default executable class to classification algorithms.
MajorityClassAssignator This class represents a ClassAssignator that determines a rule predicted class by the majority of examples covered by the rule.
NoClassAssignator  
NumericConfidenceFactor  
ProbabilisticRule  
ProbabilisticSequentialRule  
Pruner This class represents a prune procedure where one term is removed at a time, until no terms can be removed to improve the rule quality.
ReversePruner This class represents a prune procedure where one term is added at a time, until no terms can be added to improve the rule quality.
Rule This class represents a classification rule, which is built from ant tours on the problem construction graph.
SequentialRule  
Unit<V extends Comparable<V>> This class represents a unit of quality measurement for Model instances.
UnitAveragingMode<V extends Comparable<V>>  
UnitAveragingMode.DoubleUnitAveragingMode Default averaging mode for Double values.
UsefulnessHelper  
 



Copyright © 2013. All Rights Reserved.