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Gero Szepannek

Observed names: G. Szepannek, Szepannek, G., Szepannek, Gero
ORCID: 0000-0001-8456-1283
Observed ORCID: 0000-0001-8456-1283
OpenAlex ID: A5070331812
Transparency, auditability, and explainability of machine learning models in credit scoring
2021 · Michael Bücker, Gero Szepannek, et al. · Journal of the Operational Research Society · 258
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clustMixType: User-Friendly Clustering of Mixed-Type Data in R
2019 · Gero Szepannek · The R Journal · 127
Why We Should Teach Causal Inference: Examples in Linear Regression With Simulated Data
2020 · Karsten Lübke, Matthias Gehrke, et al. · Journal of Statistics Education · 39
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Imputation Strategies for Clustering Mixed-Type Data with Missing Values
2022 · Rabea Aschenbruck, Gero Szepannek, et al. · Journal of Classification · 30
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Facing the Challenges of Developing Fair Risk Scoring Models
2021 · Gero Szepannek, Karsten Lübke · Frontiers in Artificial Intelligence · 30
Clustering large mixed-type data with ordinal variables
2024 · Gero Szepannek, Rabea Aschenbruck, et al. · Advances in Data Analysis and Classification · 28
Cluster Validation for Mixed-Type Data
2020 · Aschenbruck, Rabea, Szepannek, Gero · Repository KITopen (Karlsruhe Institute of Technology) · 23
A Model Predicting Mortality of Hospitalized Covid-19 Patients Four Days After Admission: Development, Internal and Temporal-External Validation
2022 · Stefan Heber, David Pereyra, et al. · Frontiers in Cellular and Infection Microbiology · 18
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On Class Imbalance Correction for Classification Algorithms in Credit Scoring
2016 · Bernd Bischl, Tobias Kühn, et al. · Operations research proceedings · 17
Explaining Artificial Intelligence with Care: Analyzing the Explainability of Black Box Multiclass Machine Learning Models in Forensics
2022 · Gero Szepannek, Karsten Lübke · Künstliche Intell. · 12
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On the combination of locally optimal pairwise classifiers
2008 · G. Szepannek, B. Bischl, et al. · Engineering Applications of Artificial Intelligence · 11
Distances in Classification
2009 · Claus Weihs, Gero Szepannek · Lecture notes in computer science · 10
An Overview on the Landscape of R Packages for Open Source Scorecard Modelling
2022 · Gero Szepannek · Risks · 9
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Can’t see the forest for the trees: Analyzing groves to explain random forests
2023 · Gero Szepannek, Björn-Hergen von Holt · Behaviormetrika · 8
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How Much Can We See? A Note on Quantifying Explainability of Machine Learning Models
2019 · Szepannek, Gero · arXiv (Cornell University) · 8
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A customer feedback sentiment dictionary: Towards automatic assessment of online reviews
2019 · Laurens Tetzlaff, Katrin Rulle, et al. · European Journal of Tourism Research · 8
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Initialization strategies for clustering mixed-type data with the k-prototypes algorithm
2025 · Rabea Aschenbruck, Gero Szepannek, et al. · Advances in Data Analysis and Classification · 7
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Local Modelling in Classification
2008 · Gero Szepannek, Julia Schiffner, et al. · Lecture notes in computer science · 7
Local Models in Register Classification by Timbre
2006 · Claus Weihs, Gero Szepannek, et al. · Springer eBooks · 7
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An auditory model based vowel classification
2006 · Tamas Harczos, Gero Szepannek, et al. · IEEE Biomedical Circuits and Systems Conference (BioCAS) · 6
Local Modelling in Classification on Different Feature Subspaces
2006 · Gero Szepannek, Claus Weihs · Lecture notes in computer science · 6
Perceptually Based Phoneme Recognition in Popular Music
2010 · Gero Szepannek, Matthias Gruhne, et al. · Studies in classification, data analysis, and knowledge organization · 5
Extending features for automatic speech recognition by means of auditory modelling
2009 · Gero Szepannek, Tamás Harczos, et al. · 4
Variable Selection for Discrimination of More Than Two Classes Where Data are Sparse
2006 · Gero Szepannek, Claus Weihs · Springer eBooks · 4
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Schallanalyse Neuronale Repräsentation des Hörvorgangs als Basis
2005 · Gero Szepannek, Frank Klefenz, et al. · Informatik-Spektrum · 4
Works count: 82
Citation count: 710
H-index: 11
I10-index: 12
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