I think the package isnt built for training speed performance. compared with fastAdaboost its 100x slower.
set.seed(42)
fakedata <- data.frame( X=c(rnorm(100,0,1),rnorm(100,1,1)), Y=c(rep(0,100),rep(1,100) ) )
fakedata$Y <- factor(fakedata$Y)
library(adabag)
library(microbenchmark)
microbenchmark(
adab <- boosting(Y~., data=fakedata, boos=TRUE),
times = 10L
)
#20 seconds
adab
library(fastAdaboost)
microbenchmark(
fadab <- adaboost(Y~., data=fakedata, 100),
times = 10L
)
#0.2 seconds
fadab
also I don't understand your cv issue, the only way I can trigger your error is to set v higher than the number of observations in the input data.
model_2<-boosting.cv(Y~.,data=fakedata,boos=TRUE,mfinal=10,v=3)
# if v is not less than the number of observations....
model_201<-boosting.cv(Y~.,data=fakedata,boos=TRUE,mfinal=10,v=201)