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Leaf-wise Induction of Decision Tree with Presorted Deque

This is the proof-of-concept demo code for reproducing experiments in the arXiv note "A Faster Drop-in Implementation for Leaf-wise Exact Greedy Induction of Decision Tree Using Pre-sorted Deque" (https://arxiv.org/abs/1712.06989).

Prepare sample data

  • download data from HIGGS and uncompress gz file.
  • create training data head -1000000 HIGGS.csv > higgs-train-1m.csv
  • create testing data tail -50000 HIGGS.csv > higgs-test.csv

Compile and test

$ make
$ OMP_NUM_THREADS=28 ./build/test_dt higgs-train-1m.csv higgs-test.csv
tree induction time: 1.475672 seconds
training time: 2.048821 seconds
nleafs: 1845 
test metric: FP 0.276, FN 0.317, Sensitivity 0.720, Specificity 0.687, Accuracy 0.705

Other tests on synthetic data

$ OMP_NUM_THREADS=12 ./build/test_dt 
tree induction time: 1.425927 seconds
training time: 2.048105 seconds
nleafs: 24 
test metric: FP 0.801, FN 0.000, Sensitivity 1.000, Specificity 0.985, Accuracy 0.985

All rights reserved (2017-2023). Jianbo Ye

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C++ code for "A Faster Drop-in Implementation for Leaf-wise Exact Greedy Induction of Decision Tree Using Pre-sorted Deque"

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