treebagger random forest

3 次查看（过去 30 天）
Sukuchha
Sukuchha 2012-6-22
In the help file, it is stated that setting Setting 'NVarToSample' argument to any valid value but 'all' invokes Breiman's 'random forest' algorithm.
Is then, the ''OOBVarImp' will be based on GINI index as in the case of Breiman's random forest ?
How to view OOBVarImp information?
Sorry if my questions sounds dumb to you! i am dumb :)

请先登录，再回答此问题。

采纳的回答

Ilya
Ilya 2012-6-22
By setting 'OOBVarImp' to 'on', you fill OOBPermutedVarDeltaError, OOBPermutedVarDeltaMeanMargin, and OOBPermutedVarCountRaiseMargin properties of a TreeBagger object. Do 'help TreeBagger' to see a list of all properties and click on a property for a description. These three do not directly depend on the criterion used to find optimal decision splits (such as Gini). They represent three methods for computing predictor importance proposed by Breiman.
DeltaCritDecisionSplit property is always filled. It is computed by summing changes in the split criterion used to grow trees (such as Gini).
  2 个评论
Sukuchha
Sukuchha 2012-6-22
Thanks IIya
Any pointers to features selection based on tree bagger. Tutorial or similiar !
Ilya
Ilya 2012-6-22
This doc example has a short section on feature selection.
http://www.mathworks.com/help/toolbox/stats/bsvjye9.html#bsx62vu

请先登录，再进行评论。

更多回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Classification Ensembles 的更多信息

标签

产品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by