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)

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.

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.

Author

Andrzej Janusz

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).

Examples

Run this code

#######################################
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

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