DecisionTable-class: Class '"DecisionTable"'
In RoughSetKnowledgeReduction: Simplification of Decision Tables using Rough Sets

Description Objects from the Class Slots Methods Note Author(s) References See Also Examples

A decision table is a set of rules with the same number of conditions and only one decision.

Objects can be created by calls of the form new("DecisionTable", decisionTable). A decisionTable is a numeric matrix where each row is a ruleThe matrix last column is the decision of the rules and the remaining columns are rule conditions.

decisionTable:: Object of class "matrix"

checkConsistency: signature(object = "DecisionTable"): ...
computeConsistencyMatrix: signature(object = "DecisionTable"): ...
computeDiscernibilityMatrix: signature(object = "DecisionTable"): ...
findAllReductsFromCore: signature(object = "DecisionTable"): ...
findFirstConditionReduct: signature(object = "DecisionTable"): ...
findSmallestReductFamilyFromCore: signature(object = "DecisionTable"): ...
getCondition: signature(object = "DecisionTable"): ...
getDecision: signature(object = "DecisionTable"): ...
getDecisionTable: signature(object = "DecisionTable"): ...
getRule: signature(object = "DecisionTable"): ...
initialize: signature(.Object = "DecisionTable"): ...
print: signature(x = "DecisionTable"): ...
removeDuplicatedRulesDT: signature(object = "DecisionTable"): ...
show: signature(object = "DecisionTable"): ...
simplifyDecisionTable: signature(object = "DecisionTable"): ...

This is not a complete implementation of Rough Set theory; instead it is just the application of the theory to decision table simplification also known as knowledge reduction.

Alber Sanchez

Pawlak, Zdzislaw 1991 Rough Sets: Theoretical Aspects of Reasoning About Data Dordrecht: Kluwer Academic Publishing.

DiscernibilityMatrix ConditionReduct ValueReduct

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exampleMatrix1 <- matrix(c(1,0,2,1,1,2,2,0,0,1,0,1,0,2,1,
1,2,1,0,0,2,0,1,1,2,1,1,2,0,1,1,0,0,2,1,2,1,1,2,1),ncol = 5)
dt <- decisionTable(exampleMatrix1)