Statistical Methods with Applications in Data Mining: A Review of the Most Recent Works

Joaquim Fernando Pinto da Costa and Manuel Cabral
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Joaquim Fernando Pinto da Costa: CMUP, Departamento de Matemática, Faculdade de Ciências, Universidade do Porto, rua do Campo Alegre s/n, 4169-007 Porto, Portugal
Manuel Cabral: Departamento de Matemática, Faculdade de Ciências, Universidade do Porto, rua do Campo Alegre s/n, 4169-007 Porto, Portugal

Mathematics, 2022, vol. 10, issue 6, 1-22

Abstract: The importance of statistical methods in finding patterns and trends in otherwise unstructured and complex large sets of data has grown over the past decade, as the amount of data produced keeps growing exponentially and knowledge obtained from understanding data allows to make quick and informed decisions that save time and provide a competitive advantage. For this reason, we have seen considerable advances over the past few years in statistical methods in data mining. This paper is a comprehensive and systematic review of these recent developments in the area of data mining.

Keywords: data mining; state of the art; statistical methods; machine learning; statistical learning; deep learning (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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