Browsing by Author "Lyashko, Sergey"

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    A(n) Assumption in machine learning
    (Lviv Politechnic Publishing House, 2019-04-18) Klyushin, Dmitry; Lyashko, Sergey; Zub, Stanislav; Taras Shevchenko National University of Kyiv
    The commonly used statistical tools in machine learning are two-sample tests for verifying hypotheses on homogeneity, for example, for estimation of corpushomogeneity, testing text authorship and so on. Often, they are effective only for sufficiently large sample (n> 100) and have limited application in situations where the size of samples is small (n < 30). To solve the problem for small samples, methods of reproducing samples are often used: jackknife and bootstrap. We propose and investigate a family of homogeneity measures based on A(n) assumption that are effective both for small and large samples.