plot.varSelRF {varSelRF} | R Documentation |
Plots a varSelRF object, showing the initial variable importances, and the change in OOB error with the number of variables.
plot.varSelRF(x, nvar = NULL, ...)
x |
The varSelRF object. |
nvar |
The number of variables for which the initial variable importances should be shown. By default, only the 30 with the largest importance are shown. |
... |
Not used. |
This function is only used for its side effect of producing plots.
The OOB Error rate is biased down (and can be severely biased down) because we do (potentially many) rounds of reducing the set of predictor variables until we minimize this OOB error rate.
Ramon Diaz-Uriarte rdiaz@ligarto.org
Diaz-Uriarte, 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
varSelRF
, randomForest
,
importance
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.vs1 plot(rf.vs1)