## Why not?
library(geneorama)
## Source page:
## https://github.com/ndphillips/FFTrees
## Install if missing
if(!"FFTrees" %in% row.names(installed.packages())){
devtools::install_github("ndphillips/FFTrees")
}
## Load package
library("FFTrees")
## Define data
heart.train <- as.data.table(heart.train)
heart.test <- as.data.table(heart.test)
heartdisease <- as.data.table(heartdisease)
# Create an FFTrees object called `heart_FFT`
heart_FFT <- FFTrees(formula = diagnosis ~ ., # The variable we are predicting
data = heart.train, # Training data
data.test = heart.test, # Testing data
main = "ER Decisions", # Main label
decision.labels = c("Stable", "H Attack")) # Label for decisions
## View fitted model printed output
heart_FFT
## Fancy tree plot
plot(heart_FFT, data = "test")
heartdisease[ , .N, thal]
heartdisease[ , .N, cp]
heartdisease[ , .N, ca]
str(heart_FFT)
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