Metadata routing in scikit-learn

Metadata routing is a relatively new feature that allows you to, as the name implies, route metadata to different components in your machine learning setup. It's especially useful for things like sample_weight, which require data per row of your input to be passed along. But you can imagine many elaborate usecases such as (custom) estimators but also (custom) scorers. This video explains how they work. Scikit-learn documentation: https://scikit-learn.org/stable/metadata_routing.html Website: https://probabl.ai/ LinkedIn: https://www.linkedin.com/company/probabl Twitter: https://x.com/probabl_ai Bluesky: https://bsky.app/profile/probabl.bsky.social Discord: https://discord.probabl.ai We also host a podcast called Sample Space, which you can find on your favourite podcast player. All the links can be found here: https://rss.com/podcasts/sample-space/ #probabl