demo/MV.simpleData.R In janusza/RoughSets: Data Analysis Using Rough Set and Fuzzy Rough Set Theories

##############################################
## Example: Missing Value Completion
##############################################
## Deletion cases
dt.ex1 <- data.frame(
c(100.2, 102.6, NA, 99.6, 99.8, 96.4, 96.6, NA),
c(NA, "yes", "no", "yes", NA, "yes", "no", "yes"),
c("no", "yes", "no", "yes", "yes", "no", "yes", NA),
c("yes", "yes", "no", "yes", "no", "no", "no", "yes"))
colnames(dt.ex1) <- c("Temp", "Headache", "Nausea", "Flu")
decision.table <- SF.asDecisionTable(dataset = dt.ex1, decision.attr = 4,
indx.nominal = c(1:4))
indx1 = MV.deletionCases(decision.table)
new.decTable1 <- SF.applyDecTable(decision.table, indx1)

## The most common value
indx2 = MV.mostCommonValResConcept(decision.table)
new.decTable2 <- SF.applyDecTable(decision.table, indx2)

## Replacing missing attribute values
## by the attribute mean/common values
indx3 = MV.mostCommonVal(decision.table)
new.decTable3 <- SF.applyDecTable(decision.table, indx3)

## Global Closest Fit
indx4 = MV.globalClosestFit(decision.table)
new.decTable4 <- SF.applyDecTable(decision.table, indx4)

## Concept Closest Fit
indx5 = MV.conceptClosestFit(decision.table)
new.decTable5 <- SF.applyDecTable(decision.table, indx5)
janusza/RoughSets documentation built on May 31, 2018, 11:11 a.m.