Simple example:

# Classification Tree with rpart

library(rpart)

# grow tree

fit <- rpart(Kyphosis ~ Age + Number + Start,

     method="class", data=kyphosis)

Now I would like to know how can I measure the "importance" of each of my
three explanatory variables (Age, Number, Start) in the model?

If this was a regression model, I could have looked at p values from the
"anova" F test (between lm models with and without the variable). But what
is the equivalence of using "anova" on lm to an rpart object ?

Any pointers, insights and references to this question will be helpful.

Thanks,

Tal



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