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Interface Summary | |
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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 | |
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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 |
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