Description Usage Arguments Value Author(s) See Also Examples

View source: R/FeatureSelection.R

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`

.

1 | ```
FS.all.reducts.computation(discernibilityMatrix)
``` |

`discernibilityMatrix` |
an |

An object of a class `"ReductSet"`

.

Andrzej Janusz

`BC.discernibility.mat.RST`

, `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 36 | ```
########################################################
## 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)
``` |

```
Loading required package: Rcpp
```

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