Introduces MADQI, a label-free composite metric combining ARC, PPS, SDS, and ECE to evaluate unsupervised anomaly detection in AIS vessel data, reporting 80.37% on tested datasets.
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A Novel Evaluation Metric for Unsupervised Learning in AIS-Based Maritime Anomaly Detection: MADQI
Introduces MADQI, a label-free composite metric combining ARC, PPS, SDS, and ECE to evaluate unsupervised anomaly detection in AIS vessel data, reporting 80.37% on tested datasets.