Decision Tree: Pre-pruning and Pruning settings
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Trying to do a churn analysis. Following the parameters in the example process, only one node appears in the tree.
Are there any ways to optimally adjust the parameters for pre-pruning (minimal gain etc.) to enlarge the tree as well as prevent over-fitting?
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IngoRM Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Community Manager, RMResearcher, Member, University ProfessorPosts:1,751
RM Founder
Hi,
Sometimes it is hard for a decision tree to separate the classes and the tree collapses into a single node. Please check the following article for ideas how to change parameters to avoid this. Alternatively, you can also try a different learner of course.
Hope this helps,
Ingo
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