Gero Szepannek

According to our database, Gero Szepannek authored at least 25 papers between 2004 and 2023.

Collaborative distances:

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

2023

Imputation Strategies for Clustering Mixed-Type Data with Missing Values.

Rabea Aschenbruck, Gero Szepannek, Adalbert F. X. Wilhelm

J. Classif., April, 2023

A Survey on the Current Status of Research Data Management in Mecklenburg-Vorpommern Preliminary Results for a Questionnaire Study Among Researchers.

Max Schröder, Sascha Genehr, Rüdiger Köhling, Stefan Schmidt, Ralf Schneider, Sascha Spors, Gero Szepannek, Dagmar Waltemath, Frank Krüger

Proceedings of the 1st Conference on Research Data Infrastructure - Connecting Communities, 2023

2022

mlr3shiny - State-of-the-art machine learning made easy.

Laurens Martin Tetzlaff, Gero Szepannek

SoftwareX, December, 2022

Explaining Artificial Intelligence with Care.

Gero Szepannek, Karsten Lübke

Künstliche Intell., 2022

Transparency, auditability, and explainability of machine learning models in credit scoring.

Michael Bücker, Gero Szepannek, Alicja Gosiewska, Przemyslaw Biecek

J. Oper. Res. Soc., 2022

Teaching Machine Learning with mlr3 using Shiny.

Gero Szepannek, Laurens Martin Tetzlaff, Alexander Frahm, Karsten Lübke

Proceedings of the Third Teaching Machine Learning and Artificial Intelligence Workshop, 2022

2021

Facing the Challenges of Developing Fair Risk Scoring Models.

Gero Szepannek, Karsten Luebke

Frontiers Artif. Intell., 2021

2020

An Overview on the Landscape of R Packages for Credit Scoring.

Gero Szepannek

CoRR, 2020

2019

How Much Can We See? A Note on Quantifying Explainability of Machine Learning Models.

Gero Szepannek

CoRR, 2019

2018

clustMixType: User-Friendly Clustering of Mixed-Type Data in R.

Gero Szepannek

R J., 2018

2016

Editorial.

Gero Szepannek

Trans. Case Based Reason., 2016

2014

On Class Imbalance Correction for Classification Algorithms in Credit Scoring.

Bernd Bischl, Tobias Kühn, Gero Szepannek

Proceedings of the Operations Research Proceedings 2014, 2014

2009

On the combination of locally optimal pairwise classifiers.

Gero Szepannek, Bernd Bischl, Claus Weihs

Eng. Appl. Artif. Intell., 2009

Distances in Classification.

Claus Weihs, Gero Szepannek

Trans. Case Based Reason., 2009

Extending features for automatic speech recognition by means of auditory modelling.

Gero Szepannek, Tamás Harczos, Frank Klefenz, Claus Weihs

Proceedings of the 17th European Signal Processing Conference, 2009

2008

Local Modelling in Classification.

Gero Szepannek, Julia Schiffner, Julie Wilson, Claus Weihs

Proceedings of the Advances in Data Mining. Medical Applications, 2008

Localized Logistic Regression for Categorical Influential Factors.

Julia Schiffner, Gero Szepannek, Thierry Monthé, Claus Weihs

Proceedings of the Advances in Data Analysis, Data Handling and Business Intelligence, 2008

2006

Local Models in Register Classification by Timbre.

Claus Weihs, Gero Szepannek, Uwe Ligges, Karsten Luebke, Nils Raabe

Proceedings of the Data Science and Classification, 2006

Local Modelling in Classification on Different Feature Subspaces.

Gero Szepannek, Claus Weihs

Proceedings of the Advances in Data Mining, 2006

Vowel Classification by a Neurophysiologically Parameterized Auditory Model.

Gero Szepannek, Tamás Harczos, Frank Klefenz, András Kátai, Patrick Schikowski, Claus Weihs

Proceedings of the Advances in Data Analysis, 2006

2005

Schallanalyse Neuronale Repräsentation des Hörvorgangs als Basis.

Gero Szepannek, Frank Klefenz, Claus Weihs

Inform. Spektrum, 2005

Understanding Patterns with Different Subspace Classification.

Gero Szepannek, Karsten Luebke, Claus Weihs

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2005

Variable Selection for Discrimination of More Than Two Classes Where Data are Sparse.

Gero Szepannek, Claus Weihs

Proceedings of the From Data and Information Analysis to Knowledge Engineering, 2005

2004

Different Subspace Classification.

Gero Szepannek, Karsten Luebke

Proceedings of the Classification, 2004

Application of a Genetic Algorithm to Variable Selection in Fuzzy Clustering.

Christian Röver, Gero Szepannek

Proceedings of the Classification, 2004