Package: rtemis 1.4.2

rtemis: Schema-Driven Machine Learning and Visualization

Machine learning and visualization package with an 'S7' backend featuring comprehensive type checking and validation, observable runs, and auditable outputs. The functional API provides one-call access to supervised and unsupervised learning through train(), cluster(), and decomp(). All configuration steps are performed using setup functions and validated. A single call to train() can handle preprocessing, decomposition, hyperparameter tuning, model stacking, and testing with nested resampling. Supports 'data.frame', 'data.table', and 'tibble' inputs and parallel execution. Plot methods for trained and resampled supervised models draw interactive figures through 'rtemis.draw'. Includes native implementations of SuperLearner, RuleFit, and Linear Additive Trees, and supports conformal prediction. The package first appeared in E.D. Gennatas (2017) <https://repository.upenn.edu/entities/publication/d81892ea-3087-4b71-a6f5-739c58626d64>.

Authors:E.D. Gennatas [aut, cre, cph]