mlr

Provides a standardized S3 interface for classification, regression, clustering, and survival analysis, simplifying access to diverse R methods as highlighted in the README.

Includes built-in methods for resampling, hyperparameter tuning, and feature selection, reducing boilerplate code for reproducible workflows.

Supports configurators like iterated F-racing and sequential model-based optimization, enabling efficient hyperparameter tuning as detailed in the features list.

Connector for the Open Machine Learning server allows easy sharing of datasets and experiments, fostering collaborative research as mentioned in the introduction.