Enhancing user identification through batch averaging of independent window subsequences using smartphone and wearable data

Rouhollah Ahmadian, Mehdi Ghatee, Johan Wahlström

Abstract: Highlights•Introduced primary and mixed patterns for spatio-temporal data classification.•Addressed uncertainty due to pattern similarity and random primary pattern mixing.•Proposed the Batch Averaging Probabilities (BAP) model for robust classification.•BAP segments and classifies subsequences, averaging predictions to improve accuracy.•Theoretical proofs show BAP reduces error variance and improves performance.