IFconversion: Aggregation of primary data into Intuitionistic...

In IFMCDM: Intuitionistic Fuzzy Multi-Criteria Decision Making Methods

Aggregation of primary data into Intuitionistic Representation

Description

The IFconversion - Aggregation of primary data into Intuitionistic Representation. Reference describing the method: Jefmański (2020) doi: 10.1007/978-3-030-52348-0_4

Usage

IFconversion(
  primary,
  u = round(mean(c(min(primary[, -1], na.rm = TRUE), max(primary[, -1], na.rm =
    TRUE)))),
  u_is_neutral = TRUE
)

Arguments

primary	dataset with object names (not aggregated) in first column
u	cut level
u_is_neutral	if exact value of variable is equal to u (cut_level) the variable is treated as neutral (TRUE) or negative (FALSE)

Value

IFconversion returns the decision matrix (m x n*3) with the values of the mi ni and pi (three columns for each fuzzy representation), for the n criteria

References

Jefmański Bartłomiej, Intuitionistic Fuzzy Synthetic Measure for Ordinal Data. in: Classification and Data Analysis: Theory and Applications / Jajuga Krzysztof, Batóg Jacek, Walesiak Marek (eds.), Studies in Classification, Data Analysis, and Knowledge Organization, 2020, Cham, Springer, 53-72. doi: 10.1007/978-3-030-52348-0_4

Examples

set.seed(61222)
data<-sample(1:7,26*13*8,replace=TRUE)
dim(data)<-c(26*13,8)
nrColumns<-8
primary<-data.frame(name=rep(LETTERS,each=13),data)
inth<-IFconversion(primary)

IFMCDM documentation built on March 7, 2023, 6:43 p.m.