Synopsis
Learns only a root node of a decision tree. Can be very efficient when boosted.
Description
This operator learns decision stumps, i.e. a small decision tree with only one single split. This decision stump works on both numerical and nominal attributes.
Input
- training set: expects: ExampleSet
Output
- model:
- exampleSet:
Parameters
- criterion: Specifies the used criterion for selecting attributes and numerical splits.
- minimal size for split: The minimal size of a node in order to allow a split.
- minimal leaf size: The minimal size of all leaves.
- minimal gain: The minimal gain which must be achieved in order to produce a split.