Carolin Strobl

According to our database, Carolin Strobl authored at least 14 papers between 2005 and 2020.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2020

Conditional permutation importance revisited.

Dries Debeer, Carolin Strobl

BMC Bioinform., 2020

2015

Letter to the Editor: On the term 'interaction' and related phrases in the literature on Random Forests.

Anne-Laure Boulesteix, Silke Janitza, Alexander Hapfelmeier, Kristel Van Steen, Carolin Strobl

Briefings Bioinform., 2015

2014

A new variable importance measure for random forests with missing data.

Alexander Hapfelmeier, Torsten Hothorn, Kurt Ulm, Carolin Strobl

Stat. Comput., 2014

(Psycho-)analysis of benchmark experiments: A formal framework for investigating the relationship between data sets and learning algorithms.

Manuel J. A. Eugster, Friedrich Leisch, Carolin Strobl

Comput. Stat. Data Anal., 2014

2013

An AUC-based permutation variable importance measure for random forests.

Silke Janitza, Carolin Strobl, Anne-Laure Boulesteix

BMC Bioinform., 2013

2012

Random forest Gini importance favours SNPs with large minor allele frequency: impact, sources and recommendations.

Anne-Laure Boulesteix, Andreas Bender, Justo Lorenzo Bermejo, Carolin Strobl

Briefings Bioinform., 2012

2010

The behaviour of random forest permutation-based variable importance measures under predictor correlation.

Kristin K. Nicodemus, James D. Malley, Carolin Strobl, Andreas Ziegler

BMC Bioinform., 2010

2009

Party on!

Carolin Strobl, Torsten Hothorn, Achim Zeileis

R J., 2009

2008

Statistical issues in machine learning: towards reliable split selection and variable importance measures.

Carolin Strobl

PhD thesis, 2008

Conditional variable importance for random forests.

Carolin Strobl, Anne-Laure Boulesteix, Thomas Kneib, Thomas Augustin, Achim Zeileis

BMC Bioinform., 2008

2007

Unbiased split selection for classification trees based on the Gini Index.

Carolin Strobl, Anne-Laure Boulesteix, Thomas Augustin

Comput. Stat. Data Anal., 2007

Maximally selected Chi-squared statistics and non-monotonic associations: An exact approach based on two cutpoints.

Anne-Laure Boulesteix, Carolin Strobl

Comput. Stat. Data Anal., 2007

Bias in random forest variable importance measures: Illustrations, sources and a solution.

Carolin Strobl, Anne-Laure Boulesteix, Achim Zeileis, Torsten Hothorn

BMC Bioinform., 2007

2005

Variable Selection in Classification Trees Based on Imprecise Probabilities.

Carolin Strobl

Proceedings of the ISIPTA '05, 2005