Slow for classification on many classes

[rec3141]

Hi, I'm trying to figure out why ranger is taking longer than the equivalent command in randomForest in R. Are there options that are slowing it down? Thanks for any help.

dim(data_simple[training,])
[1] 4104   95

length(unique(as.factor(k.row)))  
[1] 704

num.trees <- 100000

#completes in < 12 hours on 1 thread
rf.out <- randomForest(x=data_simple[training,], y=as.factor(k.row), importance=TRUE, proximity=TRUE, ntree=num.trees, keep.forest=T, do.trace=100)

#predicted completion in 39 hours on 2 threads
ranger.out <- ranger(data=data.frame("classes"=as.factor(k.row),data_simple[training,]),importance="impurity", num.trees=num.trees, num.threads=2, write.forest=T, verbose=T, dependent.variable.name="classes", classification=T)

[mnwright]

There seems to be a problem for classification on many classes. I haven't yet optimised for that case, so it's likely there is a simple bottleneck somewhere. I will do some profiling next week.

[rec3141]

Thanks, I'll keep an eye out.
On Jun 16, 2016 10:10 PM, "Marvin N. Wright" notifications@github.com
wrote:

There seems to be a problem for classification on many classes. I haven't
yet optimised for that case, so it's likely there is a simple bottleneck
somewhere. I will do some profiling next week.

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