BC.LU.approximation.RST {RoughSets}

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.

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 Introduction-RoughSets.

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.

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.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