machine learning - unable to use Adaboost with R's caret package -

i'm using r's caret package implementing adaboost technique. i'm getting error while executing it.

> str(my_data) 'data.frame':   3885 obs. of  10 variables:  $ date    : factor w/ 12 levels "0","1","2","3",..: 3 3 3 3 3 3 3 3 3 3 ...  $ japan   : int  0 1 0 0 0 0 1 1 0 1 ...  $ hongkong: int  0 1 0 1 0 0 0 1 1 1 ...  $ china   : int  1 0 1 1 1 1 0 1 1 0 ...  $ india   : int  0 0 0 1 0 0 1 1 0 1 ...  $ germany : int  0 1 1 0 1 1 0 0 0 1 ...  $ france  : int  0 1 1 0 1 1 0 0 0 1 ...  $ euro    : int  0 1 1 0 1 1 0 0 0 1 ...  $ london  : int  0 1 1 0 1 1 0 0 0 1 ...  $ dowjones: int  0 1 0 1 1 1 0 0 0 1 ... > train=my_data[1:3600,]            #2015 > test=my_data[3601:3860,] 

there no problem when i'm implementing gbm caret

#1 gradient boost set.seed(995) fitcontrol_1 <- traincontrol( method = "repeatedcv", number = 4, repeats = 5) gbm_model<- train(factor(india)~date+japan+hongkong+china+germany+france+euro+london+dowjones,data=train, method = "gbm", trcontrol = fitcontrol_1,verbose=true) prediction_gbm= predict(gbm_model,test) solution <- data.frame(org_bse = test$india, gbm = prediction_gbm) 

but i'm not getting output though kept verbose=true

#2 adaboost set.seed(995) fitcontrol_2 <- traincontrol( method = "repeatedcv", number = 5, repeats = 5) ada_model<- train(factor(india)~date+japan+hongkong+china+germany+france+euro+london+dowjones,data=train,method="adaboost.m1",trcontrol = fitcontrol_2,verbose=true) prediction_ada= predict(ada_model,test) solution<-cbind(solution,ada=prediction_ada) 

i used following code reproduce problem:

library(caret) set.seed(995)  train <- data.frame(   cyl = as.factor(mtcars$cyl),   vs = as.factor(mtcars$vs),   = as.factor(mtcars$am),   gear = as.factor(mtcars$gear),   carb = as.factor(mtcars$carb))  fitcontrol_2 <- traincontrol(method = "repeatedcv", number = 2, repeats = 1) ada_model<- train(   cyl ~ vs + + gear + carb,   data = train,   method ="adaboost.m1",   trcontrol = fitcontrol_2,   verbose = true) 

for me, "adaboost.m1" training ran ten minutes before decided stop it. added tuning grid specified below, , got result within minute. recommend try adjust code in similar fashion:

library(caret) set.seed(995)  train <- data.frame(   cyl = as.factor(mtcars$cyl),   vs = as.factor(mtcars$vs),   = as.factor(mtcars$am),   gear = as.factor(mtcars$gear),   carb = as.factor(mtcars$carb))   fitgrid_2 <- expand.grid(mfinal = (1:3)*3,         # new!                          maxdepth = c(1, 3),       # ...and                          coeflearn = c("breiman")) # ...and  fitcontrol_2 <- traincontrol(method = "repeatedcv",                               number = 2,                               repeats = 1) ada_model <- train(   cyl ~ vs + + gear + carb,   data = train,   method ="adaboost.m1",   trcontrol = fitcontrol_2,   tunegrid = fitgrid_2, #and new, too!   verbose = true) 

let me know if solves problem.