Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/BasicRoughSets.R
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.
1  BC.LU.approximation.RST(decision.table, IND)

decision.table 
an object inheriting from the 
IND 
an object inheriting from the 
This function can be used as a basic building block for development of other RSTbased methods.
A more detailed explanation of this notion can be found in A.IntroductionRoughSets
.
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.
Andrzej Janusz
Z. Pawlak, "Rough Sets", International Journal of Computer and Information Sciences, vol. 11, no. 5, p. 341  356 (1982).
BC.IND.relation.RST
, BC.LU.approximation.FRST
1 2 3 4 5 6 7 8 9 10 11 12 13  #######################################
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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