Decision tree model using rpart ( classification
aajit75 <aajit75 <at> yahoo.co.in> writes:
fit <- rpart(decile ~., method="class", control=rpart.control(minsplit=min_obs_split, cp=c_c_factor), data=dtm_ip) In A and B target variable 'segment' is from the clustering data using same set of input variables , while in C target variable 'decile' is derived from behavioural variables and input variables are from profile data. Number of rows in the input table in all three cases are same.
What is the value of modeling the deciles as the target? They are a lower resolution version of information you already have, and without this model that doesn't finish fitting you should already be able to assign a decile to every customer. Andrew