fast_rgf
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Multi-core implementation of Regularized Greedy Forest
Is it possible to use MAE or a custom loss function as the objective/loss function for this? Examples of other tree based learners that do this or something similar are:...
HI: would you provide a windows version? thanks
download -> ``` cd build/ cmake .. ``` outputs: ``` [ 52%] Linking CXX executable forest_train CMakeFiles/forest_train.dir/forest_train.cpp.o: In function `TestOutput::print_outputs(rgf::DecisionForest&, int, int)': forest_train.cpp:(.text._ZN10TestOutputItihE13print_outputsERN3rgf14DecisionForestItihEEii[_ZN10TestOutputItihE13print_outputsERN3rgf14DecisionForestItihEEii]+0xadd): undefined reference to `pthread_create' ../forest/libforest.a(forest.cpp.o): In function...
Training is very fast, why testing is so slow? It seems the whole testing procedure is single thread, but why the console output "using up to 12 threads" during testing?
I don't see a tests folder. I'm assuming you have regression testing code in your office. Will you make part of this available as a posts-installation test harness?
/usr/bin/make64 MAC=64 [ 8%] Building CXX object src/base/CMakeFiles/base.dir/utils.cpp.o cc1plus: error: unrecognized command line option "-std=c++11" cc1plus: error: unrecognized command line option "-std=c++11" make64[2]: **\* [src/base/CMakeFiles/base.dir/utils.cpp.o] Error 1 make64[1]: **\* [src/base/CMakeFiles/base.dir/all]...