# FS.one.reduct.computation: Computing one reduct from a discernibility matrix In RoughSets: Data Analysis Using Rough Set and Fuzzy Rough Set Theories

## Description

It is a function for computing one reduct from a discernibility matrix - it can use the greedy heuristic or a randomized (Monte Carlo) search.

## Usage

 `1` ```FS.one.reduct.computation(discernibilityMatrix, greedy = TRUE, power = 1) ```

## Arguments

 `discernibilityMatrix` a `"DiscernibilityMatrix"` class representing the discernibility matrix of RST and FRST. `greedy` a boolean value indicating whether the greedy heuristic or a randomized search should be used in computations. `power` a numeric representing a parameter of the randomized search heuristic.

## Value

A class `"ReductSet"`.

Andrzej Janusz

## References

Jan G. Bazan, Hung Son Nguyen, Sinh Hoa Nguyen, Piotr Synak, and Jakub Wroblewski, "Rough Set Algorithms in Classification Problem", Chapter 2 In: L. Polkowski, S. Tsumoto and T.Y. Lin (eds.): Rough Set Methods and Applications Physica-Verlag, Heidelberg, New York, p. 49 - 88 ( 2000).

`BC.discernibility.mat.RST` and `BC.discernibility.mat.FRST`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35``` ```######################################################## ## Example 1: Generate one reducts and ## a new decision table using RST ######################################################## data(RoughSetData) decision.table <- RoughSetData\$hiring.dt ## build the decision-relation discernibility matrix res.1 <- BC.discernibility.mat.RST(decision.table, range.object = NULL) ## generate all reducts reduct <- FS.one.reduct.computation(res.1) ## generate new decision table new.decTable <- SF.applyDecTable(decision.table, reduct, control = list(indx.reduct = 1)) ############################################################## ## Example 2: Generate one reducts and ## a new decision table using FRST ############################################################## data(RoughSetData) decision.table <- RoughSetData\$hiring.dt ## build the decision-relation discernibility matrix control <- list(type.relation = c("crisp"), type.aggregation = c("crisp"), t.implicator = "lukasiewicz", type.LU = "implicator.tnorm") res.2 <- BC.discernibility.mat.FRST(decision.table, type.discernibility = "standard.red", control = control) ## generate single reduct reduct <- FS.one.reduct.computation(res.2) ## generate new decision table new.decTable <- SF.applyDecTable(decision.table, reduct, control = list(indx.reduct = 1)) ```