Ghent University Academic Bibliography

Your filters: cql: author="De Weerdt, Jochen" or (type any "bookEditor issueEditor" and editor="De Weerdt, Jochen")

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Validation set sampling strategies for predictive process monitoring

Jari Peeperkorn, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2024) INFORMATION SYSTEMS. 121.
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Hellinger distance decision trees for PU learning in imbalanced data sets

Carlos Ortega Vázquez, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2024) MACHINE LEARNING. 113(7). p.4547-4578
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GeoRF : a geospatial random forest

Margot Geerts, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2024) DATA MINING AND KNOWLEDGE DISCOVERY. 38(6). p.3414-3448
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Graph neural networks for house price prediction : do or don't?

Margot Geerts, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2024) INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS.
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LS-ICE : a load state intercase encoding framework for improved predictive monitoring of business processes

Björn Rafn Gunnarsson, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2024) INFORMATION SYSTEMS. 125.
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- Journal Article
- A1
- open access
A two-step anomaly detection based method for PU classification in imbalanced data sets

Carlos Ortega Vázquez, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2023) DATA MINING AND KNOWLEDGE DISCOVERY. 37(3). p.1301-1325
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- Conference Paper
- C1
- open access
An evolutionary geospatial regression tree

Margot Geerts, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2023) STRL 2023 : spatio-temporal reasoning and learning 2023. In CEUR workshop proceedings 3475.
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- Journal Article
- A1
- open access
A survey of methods and input data types for house price prediction

Margot Geerts, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2023) ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION. 12(5).
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Global conformance checking measures using shallow representation and deep learning

Jari Peeperkorn, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2023) ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE. 123(Part B).
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Can recurrent neural networks learn process model structure?

Jari Peeperkorn, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2023) JOURNAL OF INTELLIGENT INFORMATION SYSTEMS. 61(1). p.27-51

Academic Bibliography

Validation set sampling strategies for predictive process monitoring

Hellinger distance decision trees for PU learning in imbalanced data sets

GeoRF : a geospatial random forest

Graph neural networks for house price prediction : do or don't?

LS-ICE : a load state intercase encoding framework for improved predictive monitoring of business processes

A two-step anomaly detection based method for PU classification in imbalanced data sets

An evolutionary geospatial regression tree

A survey of methods and input data types for house price prediction

Global conformance checking measures using shallow representation and deep learning

Can recurrent neural networks learn process model structure?

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