Package: brif 1.4.1
brif: A Tree and Forest Tool for Classification and Regression
Build decision trees and random forests for classification and regression. The implementation strikes a balance between minimizing computing efforts and maximizing the expected predictive accuracy, thus scales well to large data sets. Multi-threading is available through 'OpenMP' <https://gcc.gnu.org/wiki/openmp>.
Authors:
brif_1.4.1.tar.gz
brif_1.4.1.zip(r-4.5)brif_1.4.1.zip(r-4.4)brif_1.4.1.zip(r-4.3)
brif_1.4.1.tgz(r-4.4-x86_64)brif_1.4.1.tgz(r-4.4-arm64)brif_1.4.1.tgz(r-4.3-x86_64)brif_1.4.1.tgz(r-4.3-arm64)
brif_1.4.1.tar.gz(r-4.5-noble)brif_1.4.1.tar.gz(r-4.4-noble)
brif_1.4.1.tgz(r-4.4-emscripten)brif_1.4.1.tgz(r-4.3-emscripten)
brif.pdf |brif.html✨
brif/json (API)
# Install 'brif' in R: |
install.packages('brif', repos = c('https://profyliu.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:ffda823c95. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 07 2024 |
R-4.5-win-x86_64 | OK | Nov 07 2024 |
R-4.5-linux-x86_64 | OK | Nov 07 2024 |
R-4.4-win-x86_64 | OK | Nov 07 2024 |
R-4.4-mac-x86_64 | OK | Nov 07 2024 |
R-4.4-mac-aarch64 | OK | Nov 07 2024 |
R-4.3-win-x86_64 | OK | Nov 07 2024 |
R-4.3-mac-x86_64 | OK | Nov 07 2024 |
R-4.3-mac-aarch64 | OK | Nov 07 2024 |
Exports:brifbrif_write_databrif.defaultbrif.formulabrif.trainpredictbrifTreebrifTree.defaultbrifTree.formulapredict.brifprintBrifTreeprintRulesrfpredictrftrainrftrainpredictstratpar
Dependencies:Rcpp
Readme and manuals
Help Manual
Help page | Topics |
---|---|
brif: A tree and forest tool for classification and regression | brif-package |
Build a model (and make predictions) | brif |
Write data set to file | brif_write_data |
Build a model taking a data frame as input | brif.default |
Build a model (and make predictions) with formula | brif.formula |
Train a model and use it to predict new cases | brif.trainpredict |
Build a single brif tree of a given depth | brifTree |
Build a single brif tree taking a data frame as input | brifTree.default |
Build a single brif tree taking a formula as input | brifTree.formula |
Make predictions using a brif model | predict.brif |
Print the decision rules of a Brif tree | printBrifTree |
Print the decision rules of a brif tree | printRules |
Predict new cases | rfpredict |
Train a random forest | rftrain |
Train a model and predict for newdata in one go | rftrainpredict |
Stratified permutation of rows by the first column | stratpar |