prof. dr. Seppe vanden Broucke
- ORCID iD
- 0000-0002-8781-3906
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GeoRF : a geospatial random forest
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Enhancing geospatial prediction models with feature engineering from road networks : a graph-driven approach
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Validation set sampling strategies for predictive process monitoring
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Hellinger distance decision trees for PU learning in imbalanced data sets
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- Journal Article
- A1
- open access
Explainable deep learning to classify royal navy ships
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- Conference Paper
- C1
- open access
An evolutionary geospatial regression tree
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- Conference Paper
- C1
- open access
Geospatial prediction using road topology : a graph-based perspective
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DyLoPro : profiling the dynamics of event logs
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Can recurrent neural networks learn process model structure?
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- Conference Paper
- P1
- open access
Toward data protection by design : assessing the current state of GDPR disclosure in web applications