Biography
Michel van de Velden is an associate Professor of Statistics at the Econometric Institute of the Erasmus University Rotterdam. His main research interests are exploratory data analysis. In particular, dimension reduction and cluster analysis methods with a strong focus on data visualization. In addition, he is in involved in several supervised machine learning projects involving tree-based machine learning methods.
Erasmus School of Economics
Associate professor | Econometrics
- vandevelden@ese.eur.nl
- Room
- ET-29
- Location
- Burg. Oudlaan 50, Rotterdam
More information
Work
- Rick S.H. Willemsen, Michel van de Velden & Wilco van den Heuvel (2024) - On the uniqueness of correspondence analysis solutions - doi: 10.1016/j.laa.2024.03.014 - [link]
- Michel van de Velden, Alfonso Iodice D’Enza, Angelos Markos & Carlo Cavicchia (2024) - A general framework for implementing distances for categorical variables - doi: 10.1016/j.patcog.2024.110547 - [link]
- Rick S.H. Willemsen, Wilco van den Heuvel & Michel van de Velden (2023) - A new mixed integer programming approach for inverse correspondence analysis - doi: 10.1016/j.cor.2023.106375 - [link]
- Anna Torres, Leonor Vacas de Carvalho, Joana Cesar Machado, Michel van de Velden & Patrício Costa (2023) - Exploring consumer segments defined by affective responses to naturalness in logo design - doi: 10.1108/JPBM-06-2022-4023 - [link]
- Rosaria Lombardo, Michel van de Velden & Eric J. Beh (2023) - Three-Way Correspondence Analysis in R - doi: 10.32614/RJ-2023-049 - [link]
- Sabine Knapp & Michel van de Velden (2023) - Exploration of machine learning methods for maritime risk predictions - doi: 10.1080/03088839.2023.2209788 - [link]
- Sabine Knapp & Michel van de Velden (2022) - Predicting detention and deficiencies using random forests
- Mariko Takagishi & Michel van de Velden (2022) - Visualizing Class Specific Heterogeneous Tendencies in Categorical Data - doi: 10.1080/10618600.2022.2035737 - [link]
- Pieter C. Schoonees, Patrick J.F. Groenen & Michel van de Velden (2021) - Least-squares bilinear clustering of three-way data - doi: 10.1007/s11634-021-00475-2 - [link]
- A Iodice D'Enza, Patrick Groenen & Michel van de Velden (2020) - PowerCA: A Fast Iterative Implementation of Correspondence Analysis - doi: 10.1007/978-981-15-2700-5 - [link]
EQI
- Start date approval
- juli 2022
- End date approval
- juli 2025
- Place
- ROTTERDAM
Erasmus Academie
- Start date approval
- juli 2022
- End date approval
- juli 2025
- Place
- ROTTERDAM
Applied Statistics 1
- Level
- bachelor 1
- Year Level
- bachelor 1
- Year
- 2023
- Course Code
- FEB11005X
Seminar Data Science for Marketing Analy
- Level
- master
- Year Level
- master
- Year
- 2023
- Course Code
- FEM11152
Applied Statistics 1
- Year Level
- bachelor 1, bachelor 1, bachelor 1
- Year
- 2023
- Course Code
- FEB11005