DEV Community

arun chandramouli
arun chandramouli

Posted on

Beyond Accuracy: Introducing Two Next-Generation Metrics for Real-World Machine Learning Evaluation

Traditional metrics like accuracy, precision, and recall only scratch the surface of true model performance. Today’s businesses need metrics that reflect real-world complexity and strategic impact. That’s why I’m introducing:

Model Deployment Reliability (MDR): Measures how well your model holds up in changing conditions—ensuring stability, trust, and long-term success.

Contextual Utility Index (CUI): Connects model performance directly to business value, translating predictions into measurable ROI and strategic outcomes.

https://medium.com/@chandramouliarun/beyond-accuracy-introducing-two-next-generation-metrics-for-real-world-machine-learning-evaluation-b6938db6c676

These metrics empower executives and data teams to align ML with broader organizational goals, driving sustainable innovation and tangible results.

Let’s raise the bar for how we evaluate machine learning!
hashtag#MachineLearning hashtag#AI hashtag#DataScience hashtag#MLMetrics hashtag#BusinessStrategy hashtag#Innovation hashtag#DigitalTransformation hashtag#EnterpriseAI hashtag#AIAdoption hashtag#TechLeadership

Image of Timescale

🚀 pgai Vectorizer: SQLAlchemy and LiteLLM Make Vector Search Simple

We built pgai Vectorizer to simplify embedding management for AI applications—without needing a separate database or complex infrastructure. Since launch, developers have created over 3,000 vectorizers on Timescale Cloud, with many more self-hosted.

Read full post →

Top comments (0)

Sentry image

See why 4M developers consider Sentry, “not bad.”

Fixing code doesn’t have to be the worst part of your day. Learn how Sentry can help.

Learn more