Package: agtboost 0.9.3
agtboost: 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.
Authors:
agtboost_0.9.3.tar.gz
agtboost_0.9.3.zip(r-4.5)agtboost_0.9.3.zip(r-4.4)agtboost_0.9.3.zip(r-4.3)
agtboost_0.9.3.tgz(r-4.4-x86_64)agtboost_0.9.3.tgz(r-4.4-arm64)agtboost_0.9.3.tgz(r-4.3-x86_64)agtboost_0.9.3.tgz(r-4.3-arm64)
agtboost_0.9.3.tar.gz(r-4.5-noble)agtboost_0.9.3.tar.gz(r-4.4-noble)
agtboost_0.9.3.tgz(r-4.4-emscripten)agtboost_0.9.3.tgz(r-4.3-emscripten)
agtboost.pdf |agtboost.html✨
agtboost/json (API)
NEWS
| # Install 'agtboost' in R: |
| install.packages('agtboost', repos = c('https://blunde1.r-universe.dev', 'https://cloud.r-project.org')) |
- caravan.test - The Insurance Company (TIC) Benchmark
- caravan.train - The Insurance Company (TIC) Benchmark
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:742d340ce2. Checks:OK: 1 NOTE: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 07 2024 |
| R-4.5-win-x86_64 | NOTE | Nov 07 2024 |
| R-4.5-linux-x86_64 | NOTE | Nov 07 2024 |
| R-4.4-win-x86_64 | NOTE | Nov 07 2024 |
| R-4.4-mac-x86_64 | NOTE | Nov 07 2024 |
| R-4.4-mac-aarch64 | NOTE | Nov 07 2024 |
| R-4.3-win-x86_64 | NOTE | Nov 07 2024 |
| R-4.3-mac-x86_64 | NOTE | Nov 07 2024 |
| R-4.3-mac-aarch64 | NOTE | Nov 07 2024 |
Exports:gbt.complexitygbt.convergencegbt.importancegbt.ksvalgbt.loadgbt.savegbt.train
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Adaptive and automatic gradient boosting computations. | agtboost |
| The Insurance Company (TIC) Benchmark | caravan.test caravan.train |
| Return complexity of model in terms of hyperparameters. | gbt.complexity |
| Convergence of agtboost model. | gbt.convergence |
| Importance of features in a model. | gbt.importance |
| Kolmogorov-Smirnov validation of model | gbt.ksval |
| Load an aGTBoost Model | gbt.load |
| Save an aGTBoost Model | gbt.save |
| aGTBoost Training. | gbt.train |
| aGTBoost Prediction | predict.Rcpp_ENSEMBLE |
| aGTBoost Count-Regression Auto Prediction | predict.Rcpp_GBT_COUNT_AUTO |
