FS.all.reducts.computation: A function for computing all decision reducts of a decision system

Description

A wrapper function used for generating all decision reducts of a decision system. The reducts are obtained from a discernibility matrix which can be computed using methods based on RST and FRST. Therefore, it should be noted that before calling the function, we need to compute a discernibility matrix using BC.discernibility.mat.RST or BC.discernibility.mat.FRST.

Usage

FS.all.reducts.computation(discernibilityMatrix)

Value

An object of a class "ReductSet".

Arguments

discernibilityMatrix: an "DiscernibilityMatrix" object representing a discernibility matrix of a decision system.

Author

Andrzej Janusz

Examples

Run this code

########################################################
## Example 1: Generate all reducts and
##            a new decision table using RST
########################################################
data(RoughSetData)
decision.table <- RoughSetData$hiring.dt

## build the decision-relation discernibility matrix
res.2 <- BC.discernibility.mat.RST(decision.table, range.object = NULL)

## generate all reducts
reduct <- FS.all.reducts.computation(res.2)

## generate new decision table
new.decTable <- SF.applyDecTable(decision.table, reduct, control = list(indx.reduct = 1))

##############################################################
## Example 2: Generate all reducts and
##            a new decision table using FRST
##############################################################
if (FALSE) data(RoughSetData)
decision.table <- RoughSetData$hiring.dt

## build the decision-relation discernibility matrix
control.1 <- list(type.relation = c("crisp"),
                type.aggregation = c("crisp"),
                t.implicator = "lukasiewicz", type.LU = "implicator.tnorm")
res.1 <- BC.discernibility.mat.FRST(decision.table, type.discernibility = "standard.red",
                                    control = control.1)

## generate single reduct
reduct <- FS.all.reducts.computation(res.1)

## generate new decision table
new.decTable <- SF.applyDecTable(decision.table, reduct, control = list(indx.reduct = 1))