Stability Assessment of Statistical Learning Methods in R

Overview

The R package stablelearner provides:

  • Stability assessment for tree learners: stabletree and accompanying methods, including coercion functions for various random forest objects to stabletree objects.

  • Stability assessment for supervised statistical learners in general: stability and accompanying methods, including a broad range of similarity measures for both classification and regression problems.

References

Philipp M, Zeileis A, Strobl C (2016). “A Toolkit for Stability Assessment of Tree-Based Learners.” In Colubi A, Blanco A, Gatu C (eds.), Proceedings of COMPSTAT 2016 - 22nd International Conference on Computational Statistics, 315-325. ISBN 978-90-73592-36-0. Preprint available at https://EconPapers.RePEc.org/RePEc:inn:wpaper:2016-11

Philipp M, Rusch T, Hornik K, Strobl C (2018). “Measuring the Stability of Results from Supervised Statistical Learning.” Journal of Computational and Graphical Statistics, 27(4), 685-700. doi:10.1080/10618600.2018.1473779

Installation

The stable version of stablelearner is available from CRAN:

install.packages("stablelearner")

The latest development version can be installed from R-universe:

install.packages("stablelearner", repos = "https://zeileis.R-universe.dev")

License

The package is available under the General Public License version 3 or version 2