Description Usage Arguments Value Author(s) References See Also Examples
Returns error rate and stability measures of a varSelRFBoot object.
1 2 3 4 
object 
An object of class varSelRFBoot, as returned from

return.model.freqs 
If TRUE return a table with the frequencies of the final "models" (sets of selected variables) over all bootstrap replications. 
return.class.probs 
If TRUE return average class probabilities
for each sample based on the outofbag probabilites (see

return.var.freqs.b.models 
If TRUE return the frequencies of all variables selected from the bootstrap replicates. 
... 
Not used. 
If return.class.probs = TRUE
a matrix with the average class
probabilities for each sample based on the outofbag probabilites.
Regardless of that setting, print out several summaries:
Summaries related to the "simplified" random forest on the original
data 
Such as the number and identity of the variables selected. 
Summaries related to the error rate estimate 
Such as the .632+ estimate, and some of its components 
Summaries related to the stability (uniqueness) of the results
obtained 
Such as the frequency of the selected variables in the
bootstrap runs, the frequency of the selected variables in the
boostrap runs that are also among the variables selected from the
complete run, the overlap of the bootstrap forests with the forest
from the original data set (see 
Ramon DiazUriarte rdiaz02@gmail.com
Breiman, L. (2001) Random forests. Machine Learning, 45, 5–32.
DiazUriarte, R. and Alvarez de Andres, S. (2005) Variable selection from random forests: application to gene expression data. Tech. report. http://ligarto.org/rdiaz/Papers/rfVS/randomForestVarSel.html
Efron, B. & Tibshirani, R. J. (1997) Improvements on crossvalidation: the .632+ bootstrap method. J. American Statistical Association, 92, 548–560.
randomForest
,
varSelRF
,
varSelRFBoot
,
plot.varSelRFBoot
,
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18  ## Not run:
## This is a small example, but can take some time.
x < matrix(rnorm(25 * 30), ncol = 30)
x[1:10, 1:2] < x[1:10, 1:2] + 2
cl < factor(c(rep("A", 10), rep("B", 15)))
rf.vs1 < varSelRF(x, cl, ntree = 200, ntreeIterat = 100,
vars.drop.frac = 0.2)
rf.vsb < varSelRFBoot(x, cl,
bootnumber = 10,
usingCluster = FALSE,
srf = rf.vs1)
rf.vsb
summary(rf.vsb)
plot(rf.vsb)
## End(Not run)

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.