Web: http://arxiv.org/abs/2201.02469

Jan. 10, 2022, 2:10 a.m. | Michele Bennett, Karin Hayes, Ewa J. Kleczyk, Rajesh Mehta

cs.LG updates on arXiv.org arxiv.org

Data scientists and statisticians are often at odds when determining the best
approach, machine learning or statistical modeling, to solve an analytics
challenge. However, machine learning and statistical modeling are more cousins
than adversaries on different sides of an analysis battleground. Choosing
between the two approaches or in some cases using both is based on the problem
to be solved and outcomes required as well as the data available for use and
circumstances of the analysis. Machine learning and statistical modeling are
complementary, based on similar mathematical principles, but simply …

analytics arxiv healthcare learning machine machine learning modeling statistical statistical modeling

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