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Gero Szepannek

Statistiker

Name	Gero Szepannek
Place	Deutschland
Gender	männlich
Academic degree	Prof. Dr. rer. nat.
Profession	Statistiker (characteristic profession)
Related	Technische Universität Dortmund. Lehrstuhl Computergestützte Statistik (Wissenschaftlicher Mitarbeiter) (2004-2009) Fachhochschule Stralsund. Fachbereich Wirtschaft (Professor für Statistik und Wirtschaftsmathematik) (2016-)
Source	Homepage: http://www.fh-stralsund.de/ueber-uns/personenverzeichnis/?i=877 (Stand: 05.04.2017) Homepage: https://www.researchgate.net/profile/Gero_Szepannek (Stand: 05.04.2017) Homepage: https://de.linkedin.com/in/gero-szepannek-03497787 (Stand: 05.04.2017)
Record type	Person
GND-Identifier	112928476X
Record ID	112928476X
Involved in show all Clustering large mixed-type data with ordinal variables Expanding the Scope of the k-Prototypes Algorithm - Addressing Issues in Cluster Analysis of Mixed-Type Data Arising from Real-World Applications Can’t see the forest for the trees : Analyzing groves to explain random forests A Survey on the Current Status of Research Data Management in Mecklenburg-Vorpommern : Preliminary Results for a Questionnaire Study Among Researchers Imputation Strategies for Clustering Mixed-Type Data with Missing Values Explaining Artificial Intelligence with Care : Analyzing the Explainability of Black Box Multiclass Machine Learning Models in Forensics Digital oder Real: Analyse präferierter Lehrformate von Studierenden : die hochschullehre 9/2022 Post cochlea processing : Mustererkennung zur Informationsextraktion aus simulierten Aktionspotenzialen des Hörnervs Local Modelling in Classification on Different Feature Subspaces Variable selection for discrimination of more than two classes where data are sparse Application of a Genetic Algorithm to Variable Selection in Fuzzy Clustering Different Subspace Classification

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Gero Szepannek

Clustering large mixed-type data with ordinal variables

Expanding the Scope of the k-Prototypes Algorithm - Addressing Issues in Cluster Analysis of Mixed-Type Data Arising from Real-World Applications

Can’t see the forest for the trees : Analyzing groves to explain random forests

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

Imputation Strategies for Clustering Mixed-Type Data with Missing Values

Explaining Artificial Intelligence with Care : Analyzing the Explainability of Black Box Multiclass Machine Learning Models in Forensics

Digital oder Real: Analyse präferierter Lehrformate von Studierenden : die hochschullehre 9/2022

Post cochlea processing : Mustererkennung zur Informationsextraktion aus simulierten Aktionspotenzialen des Hörnervs

Local Modelling in Classification on Different Feature Subspaces

Variable selection for discrimination of more than two classes where data are sparse

Application of a Genetic Algorithm to Variable Selection in Fuzzy Clustering

Different Subspace Classification