Hi, I've a question about the RandomForest package. The package allows the extraction of a variable importance measure. As far as I could see from the documentation, the computation is based on the Gini index. Do you know if this extraction can be also based on other criteria? In particular, I'm interested in the info gain criterion. Best regards, Chris --
ariable Importance Measure in Package RandomForest
3 messages · linuxkaffee at gmx.net, Uwe Ligges, Liaw, Andy
1 day later
Given you do not want to touch the randomForest implementation itself, the answer is "no, there is no particular function to do it in package randomForest. More particular: ?randomForest tells us that a value "importance" is returned that is `a matrix with nclass + 2 (for classification) or two (for regression) columns. For classification, the first nclass columns are the class-specific measures computed as mean descrease in accuracy. The nclass + 1st column is the mean descrease in accuracy over all classes. The last column is the mean decrease in Gini index. For Regression, the first column is the mean decrease in accuracy and the second the mean decrease in MSE. If importance=FALSE, the last measure is still returned as a vector.' So as far as I can see, you would have to change randomForest itself that has to return some relevant values in order to calculate the criterion(s) you are interested in. Best wishes, Uwe Ligges
linuxkaffee at gmx.net wrote:
Hi, I've a question about the RandomForest package. The package allows the extraction of a variable importance measure. As far as I could see from the documentation, the computation is based on the Gini index. Do you know if this extraction can be also based on other criteria? In particular, I'm interested in the info gain criterion. Best regards, Chris --
______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
The randomForest package is based on Breiman & Cutler's original code, which grows trees using the CART algorithm. The Gini criterion for splitting nodes is hard-coded in the Fortran. If you want info gain as measure of variable importance, you should be growing trees using that as the splitting criterion. It may (or may not) be possible with the party package, as that's a more modular design. That's something you can look into. Best, Andy From: Uwe Ligges
Given you do not want to touch the randomForest implementation itself, the answer is "no, there is no particular function to do it in package randomForest. More particular: ?randomForest tells us that a value "importance" is returned that is `a matrix with nclass + 2 (for classification) or two (for regression) columns. For classification, the first nclass columns are the class-specific measures computed as mean descrease in accuracy. The nclass + 1st column is the mean descrease in accuracy over all classes. The last column is the mean decrease in Gini index. For Regression, the first column is the mean decrease in accuracy and the second the mean decrease in MSE. If importance=FALSE, the last measure is still returned as a vector.' So as far as I can see, you would have to change randomForest itself that has to return some relevant values in order to calculate the criterion(s) you are interested in. Best wishes, Uwe Ligges linuxkaffee at gmx.net wrote:
Hi, I've a question about the RandomForest package. The package allows the extraction of a variable importance
measure. As far as
I could see from the documentation, the computation is
based on the Gini index.
Do you know if this extraction can be also based on other
criteria? In particular,
I'm interested in the info gain criterion. Best regards, Chris --
______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
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