Tree-based SIMCA for dealing with heterogeneous and sparse data
URF-SIMCA offers an easy to use extension of SIMCA, which deflates the variance of the target class, allowing for better separation. The increased modelling performance comes at the cost of feature interpretation, but this can be tackled using the pseudo-sampling principle.
Authors
- Robert van Vorstenbosch (ORCID: https://orcid.org/0000-0003-1953-0207)
- Zlatan Mujagic (ORCID: https://orcid.org/0000-0001-5211-0381)
- Frederik‐Jan van Schooten (ORCID: https://orcid.org/0000-0001-8111-8198)
- Agnieszka Smolinska
Institutions
- Maastricht University Medical Centre (NL)
- Maastricht University (NL)
Publication Details
- Journal
- Analytica Chimica Acta
- Published
- 2025-11-14
- DOI
- https://doi.org/10.1016/j.aca.2025.344889
- Primary Topic
- Sparse and Compressive Sensing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00