Silke Janitza

Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics

Anne‐Laure Boulesteix, Silke Janitza, Jochen Kruppa et al. · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · 2012 · 925 citations · Full text

Computing, Bioinformatics, Biostatistics +9

On the overestimation of random forest’s out-of-bag error

Silke Janitza, Roman Hornung · PLoS ONE · 2018 · 276 citations · Full text

Computing, Bioinformatics, Data Mining +14

An AUC-based permutation variable importance measure for random forests

Silke Janitza, Carolin Strobl, Anne‐Laure Boulesteix · BMC Bioinformatics · 2013 · 262 citations · Full text

Computing, Data Science, Data Mining +13

Random forest for ordinal responses: Prediction and variable selection

Silke Janitza, Gerhard Tutz, Anne‐Laure Boulesteix · Computational Statistics & Data Analysis · 2015 · 226 citations

Computing, Biostatistics, Decision Sciences +14

A computationally fast variable importance test for random forests for high-dimensional data

Silke Janitza, Ender Celik, Anne‐Laure Boulesteix · Advances in Data Analysis and Classification · 2016 · 202 citations · Full text

Computing, Biostatistics, Data Science +12