berndbischl/mlr: Machine Learning in R
Version 2.12

Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations common in machine learning, also allowing for easy nested resampling. Most operations can be parallelized.

Getting started

Package details

LicenseBSD_2_clause + file LICENSE
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
berndbischl/mlr documentation built on Oct. 13, 2017, 9:25 a.m.