PrInDTMulevAll {PrInDT} | R Documentation |
Conditional inference tree (ctree) for multiple classes on all observations
Description
ctree for more than 2 classes on all observations. Interpretability is checked (see 'ctestv').
Usage
PrInDTMulevAll(datain, classname, ctestv=NA, conf.level=0.95)
Arguments
datain |
Input data frame with class factor variable 'classname' and the |
classname |
Name of class variable (character) |
ctestv |
Vector of character strings of forbidden split results; |
conf.level |
(1 - significance level) in function |
Details
Standard output can be produced by means of print(name)
or just name
as well as plot(name)
where 'name' is the output data
frame of the function.
Value
- treeall
ctree based on all observations
- baAll
balanced accuracy of 'treeall'
- interpAll
criterion of interpretability of 'treeall' (TRUE / FALSE)
- confAll
confusion matrix of 'treeall'
Examples
datastrat <- PrInDT::data_zero
data <- na.omit(datastrat)
ctestv <- rbind('ETH == {C2a,C1a}', 'MLU == {1, 3}')
data$rel[data$ETH %in% c("C1a","C1b","C1c") & data$real == "zero"] <- "zero1"
data$rel[data$ETH %in% c("C2a","C2b","C2c") & data$real == "zero"] <- "zero2"
data$rel[data$real == "realized"] <- "real"
data$rel <- as.factor(data$rel) # rel is new class variable
data$real <- NULL # remove old class variable
conf.level <- 0.99 # 1 - significance level (mincriterion) in ctree
outAll <- PrInDTMulevAll(data,"rel",ctestv,conf.level)
outAll # print model based on all observations
plot(outAll)