Gero Szepannek

30 papers A* 3Journal 14Unranked 12
YearRankTypeTitle / Venue / Authors
2025 J jnl
Clustering large mixed-type data with ordinal variables.
Adv. Data Anal. Classif.
Gero Szepannek, Rabea Aschenbruck, Adalbert F. X. Wilhelm
2025 — conf
Explanation Groves - Controlling the Trade-off between the Degree of Explanation vs. its Complexity.
xAI (Late-breaking Work, Demos, Doctoral Consortium)
Gero Szepannek
2023 — conf
A Survey on the Current Status of Research Data Management in Mecklenburg-Vorpommern Preliminary Results for a Questionnaire Study Among Researchers.
CoRDI
Max Schröder, Sascha Genehr, Rüdiger Köhling, Stefan Schmidt, Ralf Schneider, Sascha Spors, Gero Szepannek, Dagmar Waltemath, Frank Krüger
2023 J jnl
Imputation Strategies for Clustering Mixed-Type Data with Missing Values.
J. Classif.
Rabea Aschenbruck, Gero Szepannek, Adalbert F. X. Wilhelm
2022 J jnl
Explaining Artificial Intelligence with Care.
Künstliche Intell.
Gero Szepannek, Karsten Lübke
2022 — conf
Teaching Machine Learning with mlr3 using Shiny.
Teaching ML
Gero Szepannek, Laurens Martin Tetzlaff, Alexander Frahm, Karsten Lübke
2022 J jnl
Transparency, auditability, and explainability of machine learning models in credit scoring.
J. Oper. Res. Soc.
Michael Bücker, Gero Szepannek, Alicja Gosiewska, Przemyslaw Biecek
2022 J jnl
mlr3shiny - State-of-the-art machine learning made easy.
SoftwareX
Laurens Martin Tetzlaff, Gero Szepannek
2021 J jnl
Facing the Challenges of Developing Fair Risk Scoring Models.
Frontiers Artif. Intell.
Gero Szepannek, Karsten Luebke
2020 J jnl
An Overview on the Landscape of R Packages for Credit Scoring.
CoRR
Gero Szepannek
2020 J jnl
Transparency, Auditability and eXplainability of Machine Learning Models in Credit Scoring.
CoRR
Michael Bücker, Gero Szepannek, Alicja Gosiewska, Przemyslaw Biecek
2019 J jnl
How Much Can We See? A Note on Quantifying Explainability of Machine Learning Models.
CoRR
Gero Szepannek
2018 J jnl
clustMixType: User-Friendly Clustering of Mixed-Type Data in R.
R J.
Gero Szepannek
2016 J jnl
Editorial.
Trans. Case Based Reason.
Gero Szepannek
2014 — conf
On Class Imbalance Correction for Classification Algorithms in Credit Scoring.
OR
Bernd Bischl, Tobias Kühn, Gero Szepannek
2009 A* conf
Distances in Classification.
ICDM
Claus Weihs, Gero Szepannek
2009 J jnl
Distances in Classification.
Trans. Case Based Reason.
Claus Weihs, Gero Szepannek
2009 — conf
Extending features for automatic speech recognition by means of auditory modelling.
EUSIPCO
Gero Szepannek, Tamás Harczos, Frank Klefenz, Claus Weihs
2009 J jnl
On the combination of locally optimal pairwise classifiers.
Eng. Appl. Artif. Intell.
Gero Szepannek, Bernd Bischl, Claus Weihs
2008 A* conf
Local Modelling in Classification.
ICDM
Gero Szepannek, Julia Schiffner, Julie Wilson, Claus Weihs
2008 — conf
Localized Logistic Regression for Categorical Influential Factors.
GfKl
Julia Schiffner, Gero Szepannek, Thierry Monthé, Claus Weihs
2007 — conf
On the Combination of Locally Optimal Pairwise Classifiers.
MLDM
Gero Szepannek, Bernd Bischl, Claus Weihs
2006 A* conf
Local Modelling in Classification on Different Feature Subspaces.
ICDM
Gero Szepannek, Claus Weihs
2006 — ch.
Local Models in Register Classification by Timbre.
Data Science and Classification
Claus Weihs, Gero Szepannek, Uwe Ligges, Karsten Luebke, Nils Raabe
2006 — conf
Vowel Classification by a Neurophysiologically Parameterized Auditory Model.
GfKl
Gero Szepannek, Tamás Harczos, Frank Klefenz, András Kátai, Patrick Schikowski, Claus Weihs
2005 J jnl
Schallanalyse Neuronale Repräsentation des Hörvorgangs als Basis.
Inform. Spektrum
Gero Szepannek, Frank Klefenz, Claus Weihs
2005 — conf
Understanding Patterns with Different Subspace Classification.
MLDM
Gero Szepannek, Karsten Luebke, Claus Weihs
2005 — conf
Variable Selection for Discrimination of More Than Two Classes Where Data are Sparse.
GfKl
Gero Szepannek, Claus Weihs
2004 — conf
Application of a Genetic Algorithm to Variable Selection in Fuzzy Clustering.
GfKl
Christian Röver, Gero Szepannek
2004 — conf
Different Subspace Classification.
GfKl
Gero Szepannek, Karsten Luebke