Warning messages for running r script on 10-folds cross-validation classification model of customer churn -

i'm beginner in r, i'm tring customer churn data, built classification model, , tried use cross validation evaluate our model's performance, ther wrong code below:

"""

setwd("h:/r") source("cutoff-plot.r") source("classification-metrics.r") library(tree) negative.label <- "no" positive.label <- "yes" class.labels <- c(negative.label,positive.label) data.set <- read.csv("churn.csv") data.set$churn <- factor( as.numeric(data.set$churn==positive.label), levels=0:1, labels=class.labels) f <- churn ~ . n.folds <- 10 fold.idx <- sample(rep(1:n.folds, length=nrow(data.set))) p.linear <- rep(na, nrow(data.set)) p.tree <- rep(na,nrow(data.set)) (k in 1:n.folds) {   fold <- (fold.idx == k)   linear.model <- glm(f, data.set[-fold,],family=binomial)   tree.model <- tree(f, data.set[-fold,])   p.linear[fold] <- predict(linear.model,data.set[fold, ])    p.tree[fold] <- predict(tree.model,data.set[fold, ]) } yhat.linear <- compute.yhat(p.linear,threshold=0.14) yhat.tree <- compute.yhat(p.tree,threshold=0.08) y <- data.set$churn linear.stats <- summary.stats(y, yhat.linear) tree.stats <- summary.stats(y, yhat.tree) linear.stats tree.stats cutoff.plot(p.linear,y) cutoff.plot(p.tree,y) 

"""

the problem after running loop for (k in 1:n.folds) {}, there

warning messages:  1: in p.tree[fold] <- predict(tree.model, data.set[fold, ]) :    number of items replace not multiple of replacement length  2: in p.tree[fold] <- predict(tree.model, data.set[fold, ]) :    number of items replace not multiple of replacement length  3: in p.tree[fold] <- predict(tree.model, data.set[fold, ]) :    number of items replace not multiple of replacement length  4: in p.tree[fold] <- predict(tree.model, data.set[fold, ]) :    number of items replace not multiple of replacement length  5: in p.tree[fold] <- predict(tree.model, data.set[fold, ]) :    number of items replace not multiple of replacement length  6: in p.tree[fold] <- predict(tree.model, data.set[fold, ]) :    number of items replace not multiple of replacement length  7: in p.tree[fold] <- predict(tree.model, data.set[fold, ]) :    number of items replace not multiple of replacement length  8: in p.tree[fold] <- predict(tree.model, data.set[fold, ]) :    number of items replace not multiple of replacement length  9: in p.tree[fold] <- predict(tree.model, data.set[fold, ]) :    number of items replace not multiple of replacement length  10: in p.tree[fold] <- predict(tree.model, data.set[fold, ]) :     number of items replace not multiple of replacement length 

because i'm start r few days, thx , suggestions.