gbm (Q20009): Difference between revisions
From MaRDI portal
Created claim: source code repository (P339): https://github.com/cran/gbm, #quickstatements; #temporary_batch_1711027662947 |
Swh import (talk | contribs) SWHID from Software Heritage |
||||||||||||||
| Property / Software Heritage ID | |||||||||||||||
| Property / Software Heritage ID: swh:1:snp:1144ff7f51644c1081bfa190c5f567d103de7020 / rank | |||||||||||||||
Normal rank | |||||||||||||||
| Property / Software Heritage ID: swh:1:snp:1144ff7f51644c1081bfa190c5f567d103de7020 / qualifier | |||||||||||||||
| Property / Software Heritage ID: swh:1:snp:1144ff7f51644c1081bfa190c5f567d103de7020 / qualifier | |||||||||||||||
point in time: 24 January 2024
| |||||||||||||||
Latest revision as of 15:28, 21 March 2024
Generalized Boosted Regression Models
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | gbm |
Generalized Boosted Regression Models |
Statements
10 January 2024
0 references
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.
0 references
Identifiers
24 January 2024
0 references
