Geodesy

Bubble

Benchmark (surveying)

Linguistics

Philosophy

Ensemble learning

Selection (genetic algorithm)

Parallel computing

Computer science

Maximum bubble pressure method

Interface (matter)

Geography

Hyperparameter

Feature selection

Feature (linguistics)

Artificial intelligence

Cluster analysis

Machine learning

Journal of Machine Learning Research

The MLR package provides a generic, object-oriented, and extensible framework for classification, regression, survival analysis and clustering for the R language. It provides a unified interface to more than 160 basic learners and includes meta-algorithms and model selection techniques to improve and extend the functionality of basic learners with, e.g., hyperparameter tuning, feature selection, and ensemble construction. Parallel high-performance computing is natively supported. The package targets practitioners who want to quickly apply machine learning algorithms, as well as researchers who want to implement, benchmark, and compare their new methods in a structured environment.

mlr: machine learning in R