Major Description
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