This package provides a single class,
LogitBoost, which can be used
out-of-the-box like any sciki-learn estimator.
Documentation website: https://logitboost.readthedocs.io
The latest version of LogitBoost can be installed directly after cloning from GitHub.
git clone https://github.com/artemmavrin/logitboost.git cd logitboost make install
python -m pip install logitboost
This project was developed in Python 3.7, and it is tested to also work with Python 3.6.
|||Jerome Friedman, Trevor Hastie, and Robert Tibshirani. "Additive Logistic Regression: A Statistical View of Boosting". The Annals of Statistics. Volume 28, Number 2 (2000), pp. 337–374. JSTOR. Project Euclid.|