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agtboost (version 0.9.3)

Adaptive and Automatic Gradient Boosting Computations

Description

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.

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Version

Install

install.packages('agtboost')

Monthly Downloads

338

Version

0.9.3

License

GPL-3

Maintainer

Berent <c3><85>nund Str<c3><b8>mnes Lunde

Last Published

November 23rd, 2021

Functions in agtboost (0.9.3)

gbt.load

Load an aGTBoost Model
gbt.save

Save an aGTBoost Model
gbt.convergence

Convergence of agtboost model.
predict.Rcpp_ENSEMBLE

aGTBoost Prediction
gbt.complexity

Return complexity of model in terms of hyperparameters.
gbt.train

aGTBoost Training.
gbt.importance

Importance of features in a model.
caravan.train

The Insurance Company (TIC) Benchmark
agtboost

Adaptive and automatic gradient boosting computations.
predict.Rcpp_GBT_COUNT_AUTO

aGTBoost Count-Regression Auto Prediction
gbt.ksval

Kolmogorov-Smirnov validation of model