yaiVarImp: Reports or plots importance scores for yai method randomForest

Description

When method randomforest is used to build a yai object, the randomForest package computes variable importance scores. This function computes a composite of the scores and scales them using scale. By default the scores are plotted and scores themselves are invisibly returned. For classification, the scores are derived from "MeanDecreaseAccuracy" and for regression they are based in " using importance.

Usage

yaiVarImp(object, nTop=20, plot=TRUE, ...)

Value

A data frame with the rows corresponding to the randomForest built for each Y-variable and the columns corresponding to the

nTop most important Y-variables in sorted order.

Arguments

object: an object of class yai
nTop: the nTop most important variables are plotted (returned); if NA or zero, all are returned
plot: if FALSE, no plotting is done, but the scores are returned.
...: passed to the boxplot function.

Author

Nicholas L. Crookston ncrookston.fs@gmail.com

Examples

Run this code


if (require(randomForest))
{
  data(MoscowMtStJoe)

  # get the basal area by species columns
  yba  <- MoscowMtStJoe[,1:17]
  ybaB <- whatsMax(yba,nbig=7)  # see help on whatsMax
  
  ba <- cbind(ybaB,TotalBA=MoscowMtStJoe[,18])
  x <- MoscowMtStJoe[,37:64]
  x <- x[,-(4:5)]
  rf <- yai(x=x,y=ba,method="randomForest")
  
  yaiVarImp(rf)
  
  keep=colnames(yaiVarImp(rf,plot=FALSE,nTop=9))
  
  newx <- x[,keep]
  rf2 <- yai(x=newx,y=ba,method="randomForest")
  
  yaiVarImp(rf2,col="gray")
  
  compare.yai(rf,rf2)
}