Class | Description |
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ApproximatedEntityDecisionsPredictor |
Interface used to predict right (decision) side of decision rule induced under the hypothesis that all examples
belonging to lower / upper approximation or boundary of given approximated entity are positive ones and
other are negative ones.
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Condition |
Class representing one condition, which can be found in a decision rule.
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Rule |
Class representing one single decision rule.
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RulesContainer |
Class used to store decision rules induced by a rule induction algorithm for one learning memory container.
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Class | Description |
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AttributeInfo |
Class used to store and retrieve information about a single attribute.
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RulesContainer |
Class used to store decision rules induced by a rule induction algorithm for one learning memory container.
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Class | Description |
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RulesContainer |
Class used to store decision rules induced by a rule induction algorithm for one learning memory container.
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Class | Description |
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Rule |
Class representing one single decision rule.
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RulesContainer |
Class used to store decision rules induced by a rule induction algorithm for one learning memory container.
|
Class | Description |
---|---|
Rule |
Class representing one single decision rule.
|
RulesContainer |
Class used to store decision rules induced by a rule induction algorithm for one learning memory container.
|
Class | Description |
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Condition |
Class representing one condition, which can be found in a decision rule.
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FileInfo |
Class used to store additional information about the *.rules file, present in [FILEINFO] section.
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Rule |
Class representing one single decision rule.
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RulesContainer |
Class used to store decision rules induced by a rule induction algorithm for one learning memory container.
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Class | Description |
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Relation |
Class representing single relation, for example ">= 5", "= 6" or "<=".
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RulesContainer |
Class used to store decision rules induced by a rule induction algorithm for one learning memory container.
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Class | Description |
---|---|
ApproximatedEntityDecisionsPredictor |
Interface used to predict right (decision) side of decision rule induced under the hypothesis that all examples
belonging to lower / upper approximation or boundary of given approximated entity are positive ones and
other are negative ones.
|
AttributeInfo |
Class used to store and retrieve information about a single attribute.
|
Condition |
Class representing one condition, which can be found in a decision rule.
|
ConditionValidator |
Common interface for any class which can validate conditions.
|
DecisionCondition |
Interface implemented by such subtypes of
Condition whose instances can be employed as rule's decision condition
and for which the notion of a "reference value" makes sense (e.g., referring to the reference value of condition's relation). |
FileInfo |
Class used to store additional information about the *.rules file, present in [FILEINFO] section.
|
IOptimizedRule |
Interface used to optimize some functions of
Rule class |
OptRule |
Optimization of the
Rule class. |
PairCondition |
Class representing condition created on the basis of example's field of type
PairField . |
Relation |
Class representing single relation, for example ">= 5", "= 6" or "<=".
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RelationEqual |
Class representing relation "="
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Rule |
Class representing one single decision rule.
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RuleGenerationMode |
Interface used to manage rule generation mode.
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RuleGenerator |
Abstract rule generator class.
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RulesContainer |
Class used to store decision rules induced by a rule induction algorithm for one learning memory container.
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RuleStatistics |
Class used to calculate, store and get rule's statistics like support, strength, confidence etc.
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RuleStatisticsOpt |
Class used to calculate, store and get rule's statistics like support, strength, confidence etc.
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SimilarityCondition |
Class representing similarity condition.
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SingleCondition |
Class representing single condition.
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SingleConditionForPairOfValues |
Class representing single condition defined for attribute whose values are pairs of simple values (objects of type
PairField ). |
StandardVCDomLem |
Class generating decision rules according to VC-DOMLEM algorithm, which is an extension of DOMLEM algorithm,
handling not only DRSA (Dominance-based Rough Set Approach), but also VC-DRSA (Variable Consistency DRSA),
IRSA=CRSA (Indiscernibility-based Rough Set Approach=Classical Rough Set Approach) and VC-IRSA (Variable Consistency IRSA).
This rules generator class is compatible with standard single decision classes of type StandardDecisionClass and standard unions of decision classes of type StandardUnion
and uses confidence rule's statistic when searching for best condition added to the induced rule.This class supports: - IRSA + lower approximations, upper approximations or boundaries of decision classes as positive examples (rules' conditions and decisions employ relation '='); this means certain, possible and approximate rules with confidence equal to 1, induced for single decision classes - VC-IRSA + lower approximations of decision classes as positive examples (rules' conditions and decisions employ relation '='); this means certain rules with confidence possibly less than 1, induced for single decision classes - DRSA + lower approximations or upper approximations of upward or downward unions of decision classes as positive examples (rules' conditions and decisions employ relations '>=' and '<='); this means certain or possible rules with confidence equal to 1, induced for upward or downward unions of decision classes - VC-DRSA + lower approximations of upward or downward unions of decision classes as positive examples (rules' conditions and decisions employ relations '>=' and '<='); this means certain rules with confidence possibly less than 1, induced for upward or downward unions of decision classes TODO - add description of support for DRSA and approximate rules using: 1) mix of conditions from different border objects, 2) conditions taken from two border objects (one object from lower bound and one object from upper bound of considered boundary) - decision table, PCT and similarity table as learning sample (simple values, pairs of simple values and (similarity, reference value) pairs as values of examples' fields for active condition attributes / criteria) - mixed attributes and criteria (attributes with preference type assigned) for DRSA and VC-DRSA - only new (better) VC-DRSA approach, which is described in the article J. |
VCDomLem |
Class generating decision rules according to VC-DOMLEM algorithm, which is an extension of DOMLEM algorithm,
handling not only DRSA (Dominance-based Rough Set Approach), but also VC-DRSA (Variable Consistency DRSA),
IRSA=CRSA (Indiscernibility-based Rough Set Approach=Classical Rough Set Approach) and VC-IRSA (Variable Consistency IRSA).
It is possible to configure VC-DOMLEM algorithm by: changing appropriate public flags present in this class ( VCDomLem.deleteRedundantConditions , VCDomLem.deleteRedundantRules , VCDomLem.deleteNotMinimalRules ,
and VCDomLem.checkVCDRSAMeasureValueDuringMinimalityTest ) or using setting methods VCDomLem.setModeOfPositiveExamplesForDRSA(int) and VCDomLem.setModeOfPositiveExamplesForVCDRSA(int) . |
VCDomLemOpt |
Optimization of
StandardVCDomLem class. |
Class | Description |
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RulesContainer |
Class used to store decision rules induced by a rule induction algorithm for one learning memory container.
|
Class | Description |
---|---|
RulesContainer |
Class used to store decision rules induced by a rule induction algorithm for one learning memory container.
|