modeling by reducing the risks in performance estimation. This study begins with a data-efficient approach to probabilistic … parameters. In the next phase, the output from the site-adaptation model is employed to develop a probabilistic method for …

We estimate consumer preferences for "Buy Now, Pay Later" (BNPL) using a large-scale probabilistic stated choice survey …

statistical (correlation screening and ordinary least squares regression), probabilistic (Gaussian Naïve Bayes), and classical … coefficients (β ≈ 1.336 for the overdue 15+ days bucket, p < 10−22). The Naïve Bayes classifier provides a probabilistic early … the framework offers actionable insights for risk managers by identifying key risk drivers, providing probabilistic alarms …

waiting times of activities based on Pro cess event logs. Probabilistic learning is a machine learning approach that enables …