Criteria Study in Solving Data Science Classification Problems

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Akhram Khasanovich Nishanov, et. al.

Abstract

The given article examines and analyzes DATA SCIENCE, in particular, the methods and algorithms used in solving the issues of forming information systems describing objects, classification and clustering, as well as information content criteria. As a result, it was discovered that the issues of classification, clustering, and character space reduction were poorly studied in a comprehensive manner and in resource-constrained conditions. A number of criteria evaluating the efficiency, information value and reliability indicators of algorithms and methods which are widely used in solving the issues of classification, clustering and character space reduction have been thoroughly studied in this article.

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