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JuliaAI / DecisionTree.jl

Julia implementation of Decision Tree (CART) and Random Forest algorithms
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Multithread forest application to matrices #175

Closed salbert83 closed 2 years ago

salbert83 commented 2 years ago

I guess one could multithread application of a forest to a vector instead. I think it is better to do it at this level.

codecov-commenter commented 2 years ago

Codecov Report

Merging #175 (bd1a773) into master (7e090bb) will not change coverage. The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master     #175   +/-   ##
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  Coverage   89.51%   89.51%           
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  Files          10       10           
  Lines         992      992           
=======================================
  Hits          888      888           
  Misses        104      104
Impacted Files Coverage Δ
src/classification/main.jl 97.56% <100.00%> (ø)

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ablaom commented 2 years ago

For prediction in a forest I agree that it makes sense to always use multithreading. @OkonSamuel Your thoughts? (And can you please review?)

There are possiblities for multithreading in training both forests and an individual tree, but let's leave that for a separate PR. In that case we might want to make the mode of acceleration switchable (between CPU1() and CPUThreads()).l