Katrien Antonio

According to our database, Katrien Antonio authored at least 12 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Data-driven preventive maintenance for a heterogeneous machine portfolio.

Laurens Deprez, Katrien Antonio, Joachim J. Arts, Robert N. Boute

Oper. Res. Lett., March, 2023

Empirical risk assessment of maintenance costs under full-service contracts.

Laurens Deprez, Katrien Antonio, Robert N. Boute

Eur. J. Oper. Res., 2023

Neural networks for insurance pricing with frequency and severity data: a benchmark study from data preprocessing to technical tariff.

Freek Holvoet, Katrien Antonio, Roel Henckaerts

CoRR, 2023

An engine to simulate insurance fraud network data.

Bavo D. C. Campo, Katrien Antonio

CoRR, 2023

2022

When stakes are high: Balancing accuracy and transparency with Model-Agnostic Interpretable Data-driven suRRogates.

Roel Henckaerts, Katrien Antonio, Marie-Pier Côté

Expert Syst. Appl., 2022

2021

Pricing service maintenance contracts using predictive analytics.

Laurens Deprez, Katrien Antonio, Robert N. Boute

Eur. J. Oper. Res., 2021

2020

Social network analytics for supervised fraud detection in insurance.

María Óskarsdóttir, Waqas Ahmed, Katrien Antonio, Bart Baesens, Rémi Dendievel, Tom Donas, Tom Reynkens

CoRR, 2020

Model-Agnostic Interpretable and Data-driven suRRogates suited for highly regulated industries.

Roel Henckaerts, Katrien Antonio, Marie-Pier Côté

CoRR, 2020

2019

Modeling the number of hidden events subject to observation delay.

Jonas Crevecoeur, Katrien Antonio, Roel Verbelen

Eur. J. Oper. Res., 2019

Boosting insights in insurance tariff plans with tree-based machine learning.

Roel Henckaerts, Marie-Pier Côté, Katrien Antonio, Roel Verbelen

CoRR, 2019

2018

Profit maximizing logistic model for customer churn prediction using genetic algorithms.

Eugen Stripling, Seppe vanden Broucke, Katrien Antonio, Bart Baesens, Monique Snoeck

Swarm Evol. Comput., 2018

2015

Profit maximizing logistic regression modeling for customer churn prediction.

Eugen Stripling, Seppe vanden Broucke, Katrien Antonio, Bart Baesens, Monique Snoeck

Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015