Normalized Mutual Information (NMI)

Catalogue of Tools & Metrics for Trustworthy AI

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.

Overview Tools Metrics About the catalogue

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Normalized Mutual Information is a metric calculated between two clusterings and is a normalization of the Mutual Information (MI) score to scale the results between 0 (no mutual information) and 1 (perfect correlation).

About the metric

You can click on the links to see the associated metrics

Objective(s):

Performance
Transparency & explainability

Purpose(s):

Event/anomaly detection
Forecasting/prediction
Goal-driven optimisation
Interaction support/chatbots
Personalisation/recommenders
Reasoning with knowledge structures/planning
Recognition/object detection
Content generation

Lifecycle stage(s):

Verify & validate
Build & interpret model

Target users:

Developer

Risk management stage(s):

Define
Assess
Govern
Treat

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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.