Monotonic, and better, boosting скачать в хорошем качестве

Monotonic, and better, boosting

There are these moments when you actually know something about the relationship between what you're trying to predict and the data that you have. One of these situations could involve monotonicity, which demands that when a variable 'x' goes up, 'y' must go down. Or vise versa. If you're dealing with such a situation there's some good news because the boosting implementations of scikit-learn support configuring this! The video gives an example to help motivate these constraints. This whiteboard video is part of the open efforts over at probabl. To learn more you can check out website or reach out to us on social media. Website: https://probabl.ai/ LinkedIn:   / probabl   Twitter: https://x.com/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/ If you're keen to see more videos like this, you can follow us over at @probabl_ai. #probabl