BC.positive.reg.RST: Computation of a positive region

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/BasicRoughSets.R

Description

This function implements a fundamental part of RST: computation of a positive region and the degree of dependency. This function can be used as a basic building block for development of other RST-based methods. A more detailed explanation of this notion can be found in A.Introduction-RoughSets.

Usage

1
BC.positive.reg.RST(decision.table, roughset)

Arguments

decision.table

an object inheriting from the "DecisionTable" class, which represents a decision system. See SF.asDecisionTable.

roughset

an object inheriting from the "LowerUpperApproximation" class, which represents lower and upper approximations of decision classes in the data. Such objects are typically produced by calling the BC.LU.approximation.RST function.

Value

An object of a class "PositiveRegion" which is a list with the following components:

Author(s)

Andrzej Janusz

References

Z. Pawlak, "Rough Sets", International Journal of Computer and Information Sciences, vol. 11, no. 5, p. 341 - 356 (1982).

See Also

BC.IND.relation.RST, BC.LU.approximation.RST, BC.LU.approximation.FRST

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
########################################################
data(RoughSetData)
hiring.data <- RoughSetData$hiring.dt

## We select a single attribute for computation of indiscernibility classes:
A <- c(2)

## compute the indiscernibility classes:
IND.A <- BC.IND.relation.RST(hiring.data, feature.set = A)

## compute the lower and upper approximation:
roughset <- BC.LU.approximation.RST(hiring.data, IND.A)

## get the positive region:
pos.region = BC.positive.reg.RST(hiring.data, roughset)
pos.region

janusza/RoughSets documentation built on May 31, 2018, 11:11 a.m.