Hi,
Thanks for the responce, code for each case is as:
c_c_factor <- 0.001
min_obs_split <- 80
A)
fit <- rpart(segment ~., method="class",
control=rpart.control(minsplit=min_obs_split, cp=c_c_factor),
data=Beh_cluster_out)
B)
fit <- rpart(segment ~., method="class",
control=rpart.control(minsplit=min_obs_split, cp=c_c_factor),
data=profile_cluster_out)
C)
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.
Regards,
-Ajit
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