Logit Boost

[andrewdalpino]

Logit Boost is a stage-wise additive ensemble that uses regression trees to iteratively learn a logistic regression model for binary classification problems.

See

• https://web.stanford.edu/~hastie/Papers/AdditiveLogisticRegression/alr.pdf
• J. H. Friedman. (2001). Greedy Function Approximation: A Gradient Boosting Machine.
• J. H. Friedman. (1999). Stochastic Gradient Boosting.
• Y. Wei. et al. (2017). Early stopping for kernel boosting algorithms: A general analysis with localized complexities.

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