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3 papers
Anomaly Detection in High Dimensional Data
Priyanga Dilini Talagala, Rob J. Hyndman, Kate Smith-Miles
The HDoutliers algorithm is a powerful unsupervised algorithm for detecting anomalies in high-dimensional data, with a strong theoretical foundation. However, it suffers from some…
A feature-based framework for detecting technical outliers in water-quality data from in situ sensors
Priyanga Dilini Talagala, Rob J. Hyndman, Catherine Leigh +2
Outliers due to technical errors in water-quality data from in situ sensors can reduce data quality and have a direct impact on inference drawn from subsequent data analysis. Howev…
A framework for automated anomaly detection in high frequency water-quality data from in situ sensors
Catherine Leigh, Omar Alsibai, Rob J. Hyndman +9
River water-quality monitoring is increasingly conducted using automated in situ sensors, enabling timelier identification of unexpected values. However, anomalies caused by techni…