arogozhnikov / hep_ml
Machine Learning for High Energy Physics.
Why this job: topics: neural-networks, scikit-learn, machine-learning
What it does
- uniform classifiers. the classifiers with low correlation of predictions and mass (or some other variable, or even set of variables)
- measures of uniformity (see hep_ml.metrics)
- advanced losses for classification, regression and ranking for UGradientBoosting (see hep_ml.losses).
- hep_ml.reweight. reweighting multidimensional distributions
- hep_ml.splot. minimalistic sPlot-ting
Get started
pip install hep_ml- Maintenance
- Active
- Last commit 2 months ago
- Stars
- 199
- On GitHub
- Licence
- Custom
- Read before business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.8.0
- Released 16 months ago
- Built with
- Jupyter Notebook
- 83% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 65% closed
- 23 still open
- Pull requests
- 34 merged
- 0 waiting
- Releases
- 13
- 0 in the last year
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Jupyter Notebook 83%
- Python 16%
- Makefile <1%
- Batchfile <1%
Topics
- boosting-algorithms
- high-energy-physics
- machine-learning
- neural-networks
- python
- reweighting-algorithms
- scikit-learn
- splot
Project record
- JobAI libraries and models
- StatusListed
- Commits377
- Forks70
- Watching15
- Stars in 28 days0
- CreatedMay 5, 2015
- First seen by usNov 7, 2026
- CheckedNov 8, 2026