Measuring the Stability of Recursive Partitioning Methods

Michel Philipp, Thomas Rusch, Carolin Strobl, Kurt Hornik

Competence Center for Empirical Research Methods

Publication: Contribution to conference › Conference paper

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Original language	English
Publication status	Published - 2018

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http://groups.uni-paderborn.de/eim-i-fg-huellermeier/ecda2018/

1 Journal article
1 WU Working Paper

Measuring the Stability of Supervised Statistical Learning Results
Philipp, M., Rusch, T., Strobl, C. & Hornik, K., 2018, In: Journal of Computational and Graphical Statistics. 27, 4, p. 685 - 700
Publication: Scientific journal › Journal article › peer-review
Measuring the Stability of Results from Supervised Statistical Learning
Philipp, M., Rusch, T., Hornik, K. & Strobl, C., 2017, (Research Report Series / Department of Statistics and Mathematics; no. 131).
Publication: Working/Discussion Paper › WU Working Paper

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1 Science to science

Measuring the Stability of Recursive Partitioning Methods
Michel Philipp (Contributor), Thomas Rusch (Contributor), Carolin Strobl (Contributor) & Kurt Hornik (Contributor)
4 Jul 2018 → 6 Jul 2018
Activity: Talk or presentation › Science to science

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