Mastering Classical (Transductive) Conformal Prediction in Action

Leverage the full dataset efficiently for more precise probabilistic predictions

Leverage the full dataset efficiently for more precise probabilistic predictions

Conformal Prediction is a sizzling 🔥🔥🔥🔥🔥 area of research and application, garnering significant attention in both academia and industry. The number of research papers on Conformal Prediction published in 2023 alone is expected to exceed 1,000+ papers.

At the prestigious NeurIPS 2022 machine learning conference, Stanford Professor Emmanuel Candes delivered a captivating keynote address, “Conformal Prediction in 2022,” to thousands of machine learning researchers and practitioners. He concluded by saying, “Conformal inference methods are taking the academic and industrial worlds by storm. In essence, these methods provide exact prediction intervals for future observations without relying on any distributional assumptions, except for having independent and identically distributed (iid) data, or more generally, exchangeable data.”

Conformal Prediction: Revolutionizing Machine Learning Applications

Conformal Prediction has been driving critical machine learning applications at top tech companies like Microsoft Azure (in anomaly detection) for nearly a decade. Many industry leaders are exploring ways to create, develop, and deploy solutions powered by this groundbreaking technique.

Over the last 2–3 years, awareness of Conformal Prediction within the data science and tech community has skyrocketed, thanks in part to the release of popular tutorials and open-source libraries like MAPIE and Amazon Fortuna. These tools have made Conformal Prediction models accessible to anyone with just a few lines of code.

While applications have primarily focused on regression problems thus far, MAPIE’s 2023 roadmap includes implementing Conformal Prediction for binary classification. Binary classification is a cornerstone of machine learning, with applications spanning industries such as finance, healthcare, and self-driving cars. In these domains, producing robust, well-calibrated, safe, and fair predictions is — and that’s precisely where Conformal Prediction shines.

Awesome Conformal Prediction — the best, most comprehensive, professionally curated resource for all things Conformal Prediction has been adding hundreds of GitHub stars every few weeks and is a…

Valeriy Manokhin, PhD, MBA, CQF

Principal Data Scientist, PhD in Machine Learning, creator of Awesome Conformal Prediction 👍Tip: hold down the Clap icon for up x50

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