Friedman’s h-statistic, also known as the H-stat or H-index, is a metric used to analyse interactions in a machine learning model. We apply the explainable AI (XAI) method using the artemis Python package. We also explain how to interpret the interaction heatmaps and bar plots. This includes the overall, parwise, normalised and unnormalised h-stat. These can be used to understand the percentage of a feature's effect that comes through interactions with another feature and all other features.
🚀 Free Course 🚀
Signup here: https://mailchi.mp/40909011987b/signup
XAI course: https://adataodyssey.com/courses/xai-...
SHAP course: https://adataodyssey.com/courses/shap...
🚀 Companion article with link to code (no-paywall link): 🚀
https://medium.com/data-science/analy...
🚀 Useful playlists 🚀
XAI: • Explainable AI (XAI)
SHAP: • SHAP
Algorithm fairness: • Algorithm Fairness
🚀 Get in touch 🚀
Medium: / conorosullyds
Threads: https://www.threads.net/@conorosullyds
Twitter: / conorosullyds
Website: https://adataodyssey.com/
🚀 Chapters 🚀
00:00 Introduction
00:41 Application with artemis
02:54 Overall H-stat
04:02 Pairwise H-stat
05:30 Unnormalized H-stat
In questa pagina del sito puoi guardare il video online Friedman's H-statistic Python Tutorial | Artemis Package della durata di ore minuti seconda in buona qualità , che l'utente ha caricato A Data Odyssey 03 giugno 2024, condividi il link con amici e conoscenti, su youtube questo video è già stato visto 1,839 volte e gli è piaciuto 47 spettatori. Buona visione!