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tuneRF <- function(x, y, mtryStart=if(is.factor(y)) floor(sqrt(ncol(x))) else
floor(ncol(x)/3), ntreeTry=50, stepFactor=2,
improve=0.05, trace=TRUE, plot=TRUE, doBest=FALSE, ...) {
if (improve < 0) stop ("improve must be non-negative.")
classRF <- is.factor(y)
errorOld <- if (classRF) {
randomForest(x, y, mtry=mtryStart, ntree=ntreeTry,
keep.forest=FALSE, ...)$err.rate[ntreeTry,1]
} else {
randomForest(x, y, mtry=mtryStart, ntree=ntreeTry,
keep.forest=FALSE, ...)$mse[ntreeTry]
}
if (errorOld < 0) stop("Initial setting gave 0 error and no room for improvement.")
if (trace) {
cat("mtry =", mtryStart, " OOB error =",
if (classRF) paste(100*round(errorOld, 4), "%", sep="") else
errorOld, "\n")
}
oobError <- list()
oobError[[1]] <- errorOld
names(oobError)[1] <- mtryStart
for (direction in c("left", "right")) {
if (trace) cat("Searching", direction, "...\n")
Improve <- 1.1*improve
mtryBest <- mtryStart
mtryCur <- mtryStart
while (Improve >= improve) {
mtryOld <- mtryCur
mtryCur <- if (direction == "left") {
max(1, ceiling(mtryCur / stepFactor))
} else {
min(ncol(x), floor(mtryCur * stepFactor))
}
if (mtryCur == mtryOld) break
errorCur <- if (classRF) {
randomForest(x, y, mtry=mtryCur, ntree=ntreeTry,
keep.forest=FALSE, ...)$err.rate[ntreeTry,"OOB"]
} else {
randomForest(x, y, mtry=mtryCur, ntree=ntreeTry,
keep.forest=FALSE, ...)$mse[ntreeTry]
}
if (trace) {
cat("mtry =",mtryCur, "\tOOB error =",
if (classRF) paste(100*round(errorCur, 4), "%", sep="") else
errorCur, "\n")
}
oobError[[as.character(mtryCur)]] <- errorCur
Improve <- 1 - errorCur/errorOld
cat(Improve, improve, "\n")
if (Improve > improve) {
errorOld <- errorCur
mtryBest <- mtryCur
}
}
}
mtry <- sort(as.numeric(names(oobError)))
res <- unlist(oobError[as.character(mtry)])
res <- cbind(mtry=mtry, OOBError=res)
if (plot) {
plot(res, xlab=expression(m[try]), ylab="OOB Error", type="o", log="x",
xaxt="n")
axis(1, at=res[,"mtry"])
}
if (doBest)
res <- randomForest(x, y, mtry=res[which.min(res[,2]), 1], ...)
res
}
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