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arXiv Machine Learning By Imane Hocine, Asma Abboura, Soror Sahri, Abhijith Senthilkumar, Yacine Hakimi, Gr\'egoire Danoy

TSGuard: A Real-Time Framework for Detecting and Imputing Missing Data in Streaming Time Series

Read the original on arXiv Machine Learning →

TSGuard is a real‑time framework that monitors, validates, and imputes missing values in streaming time series. It uses a lightweight graph‑aware temporal imputation model combined with constraint‑aware validation, fallback estimation, and operator‑facing explanations. The system integrates detection, imputation, and domain‑aware decision making—retaining or replacing values based on physical and spatial constraints—within a broader data‑quality loop, and offers interactive tools for operators to inspect and compare imputers in real time.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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