ModelOriented/forester: Quick and Simple Tools for Training and Testing of Tree-Based Models

The forester package is an open-source AutoML package implemented in R designed for training high-quality tree-based models on tabular data. It fully supports regression, binary classification, and multiclass classification tasks, and provides a limited support for the survival analysis task. A single line of code allows the use of unprocessed datasets, informs about potential issues concerning them, and handles feature engineering automatically. Moreover, hyperparameter tuning is performed by Bayesian optimization, which provides high-quality outcomes. The results are later served as a ranked list of models. Finally, the forester package offers a vast training report, including the ranked list, a comparison of trained models, and explanations for the best one.

install.packages("remotes")
remotes::install_github("ModelOriented/forester")