The article discusses the challenges faced in evaluating anomaly detection in time series data and introduces Proximity-Aware Time series anomaly Evaluation (PATE) as a solution. PATE provides a weighted version of Precision and Recall curve and considers temporal correlations and buffer zones for a more accurate and nuanced evaluation.
