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Revision as of 12:58, 4 March 2024
Generalized Boosted Regression Models
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | gbm |
Generalized Boosted Regression Models |
Statements
10 January 2024
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An implementation of extensions to Freund and Schapire's AdaBoost algorithm and Friedman's gradient boosting machine. Includes regression methods for least squares, absolute loss, t-distribution loss, quantile regression, logistic, multinomial logistic, Poisson, Cox proportional hazards partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures (LambdaMart). Originally developed by Greg Ridgeway. Newer version available at github.com/gbm-developers/gbm3.
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