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Author

Raby Guerbaz

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Open access Aug 2026

Reliable auto insurance fraud detection using boosting and deep learning models through comprehensive predictive performance, calibration, statistical significance, and economic impact

A robust evaluation framework for identifying auto insurance fraud that incorporates boosting-based classifiers, advanced deep tabular architectures, and adaptive resampling methods is presented, showing that the optimal model depends on the target objective, whether predictive accuracy or cost-sensitive fraud detectio...

Chadia Bekkaye, Tarek Zari, Raby Guerbaz · 0 citations
Open access Aug 2026

From classical to generative AI approaches for univariate and multivariate time series forecasting with an evaluation in finance, energy, and health domains

A controlled cross-domain comparison of four representative paradigms: classical statistics (Seasonal Autoregressive Integrated Moving Average with Exogenous variables), gradient boosting machine learning (Light Gradient Boosting Machine, LightGBM), recurrent deep learning (Recurrent Neural Network, RNN), and generativ...

Mohamed Nachat, Hassan Oukhouya, S. El Melhaoui et al. · 0 citations

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