Machine Learning for High Energy Physics
Project description
hep_ml provides specific machine learning tools for purposes of high energy physics (written in python).
Main points
uniform classifiers - the classifiers with low correlation of predictions and mass (or some other variable(s))
uBoost optimized implementation inside
UGradientBoosting (with different losses, specially FlatnessLoss is very interesting)
measures of uniformity (see hep_ml.metrics)
advanced losses for classification, regression and ranking for UGradientBoosting (see hep_ml.losses).
hep_ml.nnet - theano-based neural networks
Installation
To use the repository, clone it and install with pip:
git clone https://github.com/iamfullofspam/hep_ml.git
cd hep_ml
sudo pip install .
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