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BER-PEF: Unified Human Mobility Predictability Evaluation via Bayes Error Rate Estimation

arXiv · AI, language, vision and robotics · article · Sep 3, 2026 · UTC

Human mobility predictability concerns the best prediction performance attainable from a given target and input information, but its ground truth is not directly observable on real mobility data. We present BER-PEF, a Bayes-error-rate-based framework that converts BER estimation into mobility predictability estimation and provides a unified protocol for comparing estimators without observable ground truth. The framework maps symbolic sequences, numeric trajectories, contextual features, and learned representations into a common feature--label space, then evaluates estimator outputs along contr

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