LogitBoost

This is a Python implementation of the LogitBoost classification algorithm [1] built on top of scikit-learn. It supports both binary and multiclass classification; see the examples.

This package provides the following class, which can be used out-of-the-box like any scikit-learn estimator:

LogitBoost([base_estimator, n_estimators, …])

A LogitBoost classifier.

Contents:

• Installation
• The LogitBoost Class
• Examples Using LogitBoost
• Source Code on GitHub

References

[1]	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.