I'm working with the Anderson Iris data set and it is too small To split into a test and training set.I use boosting To make a classifier For determining the species Of flower Based on Variables in The data set.
I'd like to use cross validation To Test my predictor.My understanding is that I need to make a for loop That runs The function On all but one Of the observations.
Is there a function I can use that automate this process? Am I right That Cross validation can be used To test The error rate for my boosting tree?
this is my boosting tree
library('adabag') boost <- boosting(Species~.,data=ii,boos = TRUE, mfinal=3)