mob-ai created SPARK-29224:
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Summary: Implement Factorization Machines as a ml-pipeline
component
Key: SPARK-29224
URL: https://issues.apache.org/jira/browse/SPARK-29224
Project: Spark
Issue Type: New Feature
Components: ML
Affects Versions: 2.4.3
Reporter: mob-ai
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.
Goal: Implement Factorization Machines as a ml-pipeline component
Requirements:
1. loss function supports: logloss, mse
2. optimizer: mini batch SGD
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
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