Decision Tree: Pre-pruning and Pruning settings
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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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
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.
http://community.rapidminer.com/t5/RapidMiner-Studio-Knowledge-Base/My-Decision-Tree-Shows-only-one-...
Hope this helps,
Ingo