%0 Computer Program
%A Ghorbani, Ramin
%A Reinders, Marcel
%A Tax, David
%D 2024
%T Code underlying the publication: "PATE: Proximity-Aware Time series anomaly Evaluation"
%U 
%R 10.4121/d8b0f4ab-3bd6-412b-88dd-f515d545aefd.v1
%K Time Series
%K Anomaly Detection
%K Evaluation Metrics
%K Precision
%K Recall
%X <p>This repository provides the implementation of Proximity-Aware Time Series Anomaly Evaluation (PATE), a novel metric introduced to address the limitations of existing evaluation methods for time series anomaly detection. PATE incorporates proximity-based weighting with buffer zones around anomaly intervals to account for temporal complexities such as Early or Delayed detections, Onset response time, and Coverage level. It computes a weighted version of the Area Under Precision and Recall curve, offering a more accurate and meaningful assessment of anomaly detection models. Experimental results validate PATE's ability to distinguish performance differences across various models and scenarios.</p>
%I 4TU.ResearchData