I am using the
glmtree function from the
partykit package in R.
I would like to know how I can evaluate the models and how I can improve them.
I am growing a big tree (
alpha = 0.9) and pruning with AIC as the criterion.
I am using the AUC (
pROC package) and the results are between 0.62 and 0.79.
fit <- glmtree(fD ~ 1 | Age + fGender + Qualification + fOccupation + SizeWorkplc, data = newdata, family = "binomial", minsize = 50, maxdepth = 4, alpha = 0.9, prune = "AIC") prob <- predict(fit, newdata = newdata, type "response") newdata$prob <- prob g <- roc(fD ~ prob, data = newdata) plot(g)
I am really new on this, so I would really appreciate some help.