i was implementing xgb code is like below,
bst <- xgboost(data = as.matrix(train.boost), label = lable.train, max.depth = 2, eta = 1, nthread = 2, nround = 20, objective = "binary:logistic")
so i am surprised with the result of xgb, especially with nround
nround when -> 5 it gave train-error:0.175896 [final pass]
nround when -> 10 it gave train-error:0.154723 [final pass]
nround when ->20 it gave train-error:0.114007 [final pass]
nround when ->30 it gave train-error:0.099349 [final pass]
i think when i am using nround as high number it is overfitting the data, So i am confused, I want to know how to choose ideal value of nround.