R: Genetic Algorithm Feature Selection 'replace = FALSE' error - r

Question

I am trying to implement the genetic algorithm for feature selection as done in the book Feature Engineering and Selection: A Practical Approach for Predictive Models
by Max Kuhn and Kjell Johnson. I copied the code from here https://github.com/topepo/FES/blob/master/12_Global_Search/12_03_Genetic_Algorithms.R
I keep getting this error, "cannot take a sample larger than the population when 'replace = FALSE'". For the sake of demonstration, I tried it on the churn data set. Also, I reduced the iterations from 15 to 1 to increase the speed.
library(caret)
library(liver)
data(churn)
head(churn)
set.seed(3456)
trainIndex <- createDataPartition(churn$churn, p = .8,
list = FALSE,
times = 1)
train <- churn[ trainIndex,]
test <- churn[-trainIndex,]
# ------------------------------------------------------------------------------
many_stats <-
function(data, lev = levels(data$obs), model = NULL) {
c(
twoClassSummary(data = data, lev = levels(data$obs), model),
prSummary(data = data, lev = levels(data$obs), model),
mnLogLoss(data = data, lev = levels(data$obs), model),
defaultSummary(data = data, lev = levels(data$obs), model)
)
}
# ------------------------------------------------------------------------------
ga_funcs <- caretGA
ga_funcs$fitness_extern <- many_stats
ga_funcs$initial <- function(vars, popSize, ...) {
x <- matrix(NA, nrow = popSize, ncol = vars)
probs <- seq(0.1, 0.90, length = popSize)
for (i in 1:popSize) {
x[i, ] <-
sample(0:1, replace = TRUE, size = vars, prob = c(probs[i], 1 - probs[i]))
}
var_count <- apply(x, 1, sum)
if (any(var_count == 0)) {
for (i in which(var_count == 0)) {
p <- sample(1:length(vars), size = 2)
x[i, p] <- 1
}
}
x
}
ctrl_rs <- trainControl(
method = "LGOCV",
p = 0.90,
number = 1,
summaryFunction = many_stats,
classProbs = TRUE,
allowParallel = FALSE
)
ga_ctrl <- gafsControl(
method = "cv",
metric = c(internal = "ROC", external = "ROC"),
maximize = c(internal = TRUE, external = TRUE),
functions = ga_funcs,
returnResamp = "all",
verbose = TRUE
)
options(digits = 3)
nb_grid <- data.frame(usekernel = TRUE, fL = 0, adjust = 1)
set.seed(325)
gen_algo <- gafs(
x = train[,-20],
y = train$churn,
data = train,
iters = 1,
gafsControl = ga_ctrl,
method = "nb",
tuneGrid = nb_grid,
trControl = ctrl_rs,
metric = "ROC"
)
The code specifies, "replace = TRUE", but clearly I am missing something. Any help is greatly appreciated!
Thanks!