search for: meandecreaseaccuracy

I am trying to use the random forests package for classification in R. The Variable Importance Measures listed are: -mean raw importance score of variable x for class 0 -mean raw importance score of variable x for class 1 -MeanDecreaseAccuracy -MeanDecreaseGini Now I know what these "mean" as in I know their definitions. What I want to know is how to use them. What I am trying to figure out is what these values mean in only the context of how accurate they are, what is a good value, what is a bad value, what are the maximums...

HI, Dear Andy, I run the RandomFOrest in R, and get the following resutls in variable importance: What is the meaning of MeanDecreaseAccuracy and MeanDecreaseGini? I found they are raw values, they are not scaled to 1, right? Which column if most similar to the variable rel.influence in Boosting? Thanks so much! > fit$importance 0 1 MeanDecreaseAccuracy MeanDecreaseGini CT 0.0022352...

...variables. Some of these variables are highly correlated. I believe that I understand how randomForest works and how the variable importance are evaluated (through variable permutations). Here are my questions. 1) variable importance error? Is there any ways to estimate the error on the "MeanDecreaseAccuracy"? In other words, I would like to know how significant are "MeanDecreaseAccuracy" differences (and display horizontal error bars in the VarImpPlot output). I have notice that even with relatively large number of trees, I have variation in the importance values from one run to the...

...est model and draw predictors importance plot. I used below commands: rf.fit<-randomForest(x,y,ntree=500,importance=TRUE) ## "x" is matrix whose columns are predictors, "y" is a binary resonse vector ## Then I got the ranked predictors by ranking "rf1$importance[,"MeanDecreaseAccuracy"]" ## Then draw the importance plot varImpPlot(rf.fit) As you can see, all the functions I used are directly from the package "randomForest", instead of from "caret". so I'm wondering if the package "caret" has some functions who can do the above ranking...

...'importance' element matrix has four columns with the following headings: 0 - mean raw importance score of variable x for class 0 (where importance is the difference between the permutated data error and the original test set error) 1 - mean raw importance score of variable x for class 1 MeanDecreaseAccuracy : average lowering of the margin across all cases (where margin is the proportion of votes for the true class - the maximum proportion of votes for the other classes) MeanDecreaseGini : summation of the gini decreases over all trees in the forest Are these definitions correct? Why is the raw...

...credit<-read.csv(url("ftp://ftp.ics.uci.edu/pub/machine-learning-databases/credit-screening/crx.data"), header=FALSE, na.string="?") credit.rf <- randomForest(V16~., credit, imp=T, do.trace=100,na.action=na.omit) imp <- round(importance(credit.rf), 2) imp - + MeanDecreaseAccuracy MeanDecreaseGini V1 0.00 0.00 0.00 0.00 V2 0.75 0.25 0.55 19.92 V3 0.41 0.57 0.46 22.13 V4 0.39 0.33 0.33 4.93 V5 0.26 0.24 0.21 0.60 V6 0.39 0...

Hello R Fundi, The poetic title of this post is a request for help in regard to a "simple" plotting question. I have displayed the mean observations of a series variables using barplot(). On the same figure I have colored the bars to represent the Standard deviation of each variable using color.scale(). Now I wish to add a graduated colorbar (legend) that corresponds to the colors