Adaptive and Automatic Gradient Boosting Computations

Fast and automatic gradient tree boosting designed to avoid manual tuning and cross-validation by utilizing an information theoretic approach. This makes the algorithm adaptive to the dataset at hand; it is completely automatic, and with minimal worries of overfitting. Consequently, the speed-ups relative to state-of-the-art implementations can be in the thousands while mathematical and technical knowledge required on the user are minimized.


Reference manual

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0.9.3 by Berent Ånund Strømnes Lunde, 2 months ago

Browse source code at

Authors: Berent Ånund Strømnes Lunde

Documentation:   PDF Manual  

GPL-3 license

Imports methods, Rcpp

Suggests testthat

Linking to Rcpp, RcppEigen

Imported by autostats.

See at CRAN