Enhancement : faster getTerminalNodeIDs

[pej]

Hi.
Thanks a lot for this brilliant package.
I would like to derive proximity matrices from forests built with ranger. As far as I know there is currently no direct builtin functionality to do so.
Yet the getTerminalNodeIds function might be used. Unfortunately this function (due to its crude R implementation) is quite slow compared with forest learning or predicting processes. I was wondering if you could speed it up or if the learning or predicting functions may also return the getTerminalNodeIds matrix or even better a proximity matrix ?

Thanks

[mnwright]

You are right, there is no option for the proximity matrix yet and getTerminalNodeIds() is very slow. An option would be to add this to the predict() function, e.g. by setting type = "terminalNodeID" or something similar.

[pej]

Yes this would be great to have such a functionality !

In the meantime, for those that would like to get the terminal node IDs in a faster way, you could use the following RCpp based getTerminalNodeIDs function (which should work on numeric data) :

library(Rcpp)
cppFunction('
NumericVector getTerminalNodeIDsCPP(NumericVector childNodesIDs1,NumericVector childNodesIDs2,NumericVector splitValues,NumericVector splitVarIDs,NumericMatrix mat)
{
NumericVector res(mat.nrow());
for(int i=0;i<mat.nrow();i++)
{
int nodeID = 1;
double value =0;
while (true) {
if ( (childNodesIDs1[nodeID-1] == 0 && childNodesIDs2[nodeID-1] == 0))
{
break;
}
int splitVarID = splitVarIDs[nodeID-1];
value = mat(i,splitVarID-1);//obs[splitVarID-1];
if (value <= splitValues[nodeID-1]) {
nodeID = childNodesIDs1[nodeID-1] + 1;
}
else {
nodeID = childNodesIDs2[nodeID-1] + 1;
}
}
res[i]=nodeID;
}
return(res);
}
')

getTerminalNodeIDs2<-function(data,rf)
{
res=sapply(1:rf$num.trees, function(tree) {
getTerminalNodeIDsCPP(rf$forest$child.nodeIDs[[tree]][[1]],rf$forest$child.nodeIDs[[tree]][[2]],as.double(rf$forest$split.values[[tree]]),rf$forest$split.varIDs[[tree]],as.matrix(data))
})
return(res)
}

#example
library(ranger)
rf=ranger(Species ~ ., data = iris,write.forest=T)
y1=getTerminalNodeIDs2(iris[,-5],rf)
y2=getTerminalNodeIDs(rf,iris[,-5])
identical(y1,y2)
[1] TRUE

system.time(getTerminalNodeIDs(rf,iris[,-5]))
#utilisateur système écoulé

1.551 0.016 1.613

system.time(getTerminalNodeIDs2(iris[,-5],rf))
#utilisateur système écoulé

0.033 0.001 0.034

[mnwright]

New option "terminalNodes" added to predict(), as described above.

[pej]

Thanks a lot !

On 21 September 2016 at 22:33, Marvin N. Wright notifications@github.com
wrote:

New option "terminalNodes" added to predict(), as described above.

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