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Towards Expectation-Maximization by SQL in RDBMS
[article]
2021
arXiv
pre-print
Integrating machine learning techniques into RDBMSs is an important task since there are many real applications that require modeling (e.g., business intelligence, strategic analysis) as well as querying data in RDBMSs. In this paper, we provide an SQL solution that has the potential to support different machine learning modelings. As an example, we study how to support unsupervised probabilistic modeling, that has a wide range of applications in clustering, density estimation and data
arXiv:2101.09094v1
fatcat:cidssfb2grffzkyddqbldtwmgi