Code to reproduce the experiments in the paper "Learning concise representations for regression by evolving networks of trees"
Experiments can be run using analysis/ml-analyst/submit_jobs.py
. See the command line options (python submit_jobs.py -h
) for help.
As example, this command would launch the main experiment from the paper:
python submit_jobs.py --r -ml Feat,FeatCN,FeatCorr,RandomForest,MLPmod,Kernel,Linear,XGBoostLong -n_trials 5 ../penn-ml-benchmark/datasets/regression/
analysis/
contains these notebooks:
results_iclr.ipynb
produces the main results figures.results_appendix.ipynb
produces the results comparing different stochastic optimization approaches.stats.ipynb
depends onresults_iclr.ipynb
and produces the statistical tests.archive.ipynb
contains code to reproduce the illustrative example.
- FEAT
- scikit-learn
- xgboost
- datasets come from PMLB