How to choose a validation measure for ML models: Yandex appro | Big Data Science

How to choose a validation measure for ML models: Yandex approach
Every practical machine learning problem has a problem with measuring results. Different measures can lead to different assessment results and, therefore, to different chosen algorithms. Therefore, it is very important to find a suitable measure of quality. Researchers from Yandex compare various approaches to solving typical ML problems, from classification to clustering, in order to formulate a universal method for choosing the most optimal quality measure. Key messages and main results are presented in articles at conferences In recent articles published on ICML 2021 and NeurIPS 2021, and a short retelling is available directly on the Yandex website https://research.yandex.com/news/how-to-validate-validation-measures.
http://proceedings.mlr.press/v139/gosgens21a/gosgens21a.pdf
https://papers.nips.cc/paper/2021/file/8e489b4966fe8f703b5be647f1cbae63-Paper.pdf