...how can we improve the speed of a predicting new data using a Random Forest Model in R language
This paper on the ranger package, ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R, gives a breakdown of speed depending on various factors. See the SO thread below for some more suggestions:
I have gone through this link what you have post but I can't resolve my issue.
Now also it is taking time to predict the output. I am using random forest to do it.
Thanks in advance.
It's hard to give a recommendation on this as an abstraction, here.
Could you please turn this into a self-contained reprex (short for reproducible example) with some dummy data so we can see what packages you're using, etc.?
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