Rebecca Marion
Rebecca Marion
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BIR: A method for selecting the best interpretable multidimensional scaling rotation using external variables
R Marion, A Bibal, B Frénay
Neurocomputing 342, 83-96, 2019
Finding the most interpretable MDS rotation for sparse linear models based on external features
A Bibal, R Marion, B Frénay
26th European Symposium on Artificial Neural Networks, Computational …, 2018
The essentials on linear regression, ANOVA, general linear and linear mixed models for the chemist
B Govaerts, B Francq, R Marion, M Martin, M Thiel
Ref Module Chem Mol Sci Chem Eng, 431-463, 2020
BIOT: Explaining multidimensional nonlinear MDS embeddings using the Best Interpretable Orthogonal Transformation
A Bibal, R Marion, R von Sachs, B Frénay
Neurocomputing 453, 109-118, 2021
AdaCLV for interpretable variable clustering and dimensionality reduction of spectroscopic data
R Marion, B Govaerts, R von Sachs
Chemometrics and Intelligent Laboratory Systems 206, 104169, 2020
Comparison of Cluster Validity Indices and Decision Rules for Different Degrees of Cluster Separation
S Kaczynska, R Marion, R von Sachs
ESANN, 2020
Globally local and fast explanations of t-SNE-like nonlinear embeddings
P Lambert, R Marion, J Albert, E Jean, S Corbugy, C de Bodt
2022 International Conference on Information and Knowledge Management …, 2022
VC-PCR: A Prediction Method based on Supervised Variable Selection and Clustering
R Marion, J Lederer, B Govaerts, R von Sachs
arXiv preprint arXiv:2202.00975, 2022
Pre-processing of nmr spectra: review and evaluation of baseline correction, normalization, scaling and transformation methods
R Marion
Improving the Feature Selection Stability of the Delta Test in Regression
R Marion, B Frénay
IEEE Transactions on Artificial Intelligence, 2023
Globally local and fast explanations of 𝑡-SNE-like nonlinear embeddings
P Lambert, R Marion, J Albert, E Jean, S Corbugy, C de Bodt
Statistical and Machine Learning Methods for Identifying Clusters of Variables
R Marion
Université catholique de Louvain, 2021
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