Machine learning analysis reveals which metrics drive March Madness seeding and predictive analytics in committee decisions.
Abstract: Datasets used in data analysis often contain irrelevant or redundant attributes. These attributes hinder the performance of predictive models. Therefore, an effective preprocessing feature ...
Abstract: Feature selection is a critical step in data mining, with the granular ball rough set model widely applied in this area. However, the randomness issue during the initialization of the ...
With Selection Sunday a little less than a month away, the NCAA selection committee, meeting in Indianapolis this week, has unveiled its current top-16 seeds in the NCAA tournament ahead of an ...
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