These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
Contextual Outlier Interpretation (COIN)
Contextual Outlier INterpretation (COIN) is a method designed to explain the abnormality of existing outliers spotted by detectors. The interpretability for an outlier is achieved from three aspects: outlierness score, att that contribute to the abnormality, and contextual description of its neighborhoods.
About the metric
You can click on the links to see the associated metrics
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