R: A function for computing all decision reducts of a decision...

FS.all.reducts.computation {RoughSets} | R Documentation

## 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)

### Arguments

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

### Value

An object of a class `"ReductSet"`.

### Author(s)

Andrzej Janusz

### See Also

`BC.discernibility.mat.RST`, `BC.discernibility.mat.FRST`.

### Examples

    ########################################################
    ## 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
    ##############################################################
    ## Not run: 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))
    ## End(Not run)

[Package RoughSets version 1.3-7 Index]