mob-ai opened a new pull request #25909: [SPARK-29224]Implement Factorization Machines as a ml-pipeline component URL: https://github.com/apache/spark/pull/25909 ### What changes were proposed in this pull request? Implement Factorization Machines as a ml-pipeline component 1. loss function supports: logloss, mse 2. optimizer: mini batch SGD ### Why are the changes needed? Factorization Machines is widely used in advertising and recommendation system to estimate CTR(click-through rate). Advertising and recommendation system usually has a lot of data, so we need Spark to estimate the CTR, and Factorization Machines are common ml model to estimate CTR. References: 1. S. Rendle, “Factorization machines,” in Proceedings of IEEE International Conference on Data Mining (ICDM), pp. 995–1000, 2010. https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf ### Does this PR introduce any user-facing change? No ### How was this patch tested? run unit tests
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