RoughSets (version 1.2-1)

BC.LU.approximation.RST: Computation of lower and upper approximations of decision classes

Description

This function implements a fundamental part of RST: computation of lower and upper approximations. The lower and upper approximations determine whether the objects can be certainty or possibly classified to a particular decision class on the basis of available knowledge.

Usage

BC.LU.approximation.RST(decision.table, IND)

Arguments

decision.table

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

IND

an object inheriting from the "IndiscernibilityRelation" class, which represents indiscernibility clasees in the data.

Value

• An object of a class "LowerUpperApproximation" which is a list with the following components:
  • lower.approximation: a list with indices of data instances included in lower approximations of decision classes.
  • upper.approximation: a list with indices of data instances included in upper approximations of decision classes.
  • type.model: a character vector identifying the type of model which was used. In this case, it is"RST"which means the rough set theory.

Details

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.

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.FRST

Examples

#######################################
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 approximations:
roughset <- BC.LU.approximation.RST(hiring.data, IND.A)
roughset