SAS enterprise miner decision tree splitting

Scott86 — Mon, 25 May 2020 03:16:37 GMT

Hi Everyone,

I am creating a decision tree and I want it to be only 3 nodes deep. I am controlling the splitting by using the leaf size under the Node area for Decision tree models, I am setting it to 200 (that is a minimum of 200 obs per leaf). The issue is the target I am splitting up which is binary (1 and 2) has a low volume. The target 2 only account for 0.44% of the observations. This is creating difficulty in the tree splitting. When I set the leaf size to 200 it goes to deep but when I increase it the tree does not split at all. I have tried changing the Significance level but it has no affect.

Nominal target Criterion is ProbChisq and significance level is 0.2.

Any help on how to tune the Hyper-Parameters to prune the model would be great.

Thanks

Scott

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SAS enterprise miner decision tree splitting