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Updated Trees (markdown)

Richard Townsend 2014-07-26 05:45:53 -07:00
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Trees.md

@ -7,4 +7,7 @@ ID3 is a decision tree induction algorithm which splits on the Attribute which g
Random Trees are structurally identical to those generated by ID3, but the split Attribute is chosen randomly. Golearn's implementation allows you to choose up to *k* nodes for consideration at each split.
##Random forests
Random forests are a bagged ensemble technique which combines multiple Random Trees and outputs a classification via a majority vote.
Random forests are a bagged ensemble technique which combines multiple Random Trees and outputs a classification via a majority vote.
**See also:
[`examples/knnclassifier/knnclassifier_iris.go`](https://github.com/sjwhitworth/golearn/blob/master/examples/knnclassifier/knnclassifier_iris.go)**