treebagger random forest
3 views (last 30 days)
Show older comments
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 :)
0 Comments
Accepted Answer
Ilya
on 22 Jun 2012
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 Comments
Ilya
on 22 Jun 2012
This doc example has a short section on feature selection.
http://www.mathworks.com/help/toolbox/stats/bsvjye9.html#bsx62vu
More Answers (0)
See Also
Categories
Find more on Classification Ensembles in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!