Application of Differential Evolution Algorithm Based on Mixed Penalty Function Screening Criterion in Imbalanced Data Integration Classification

Yuelin Gao, Kaiguang Wang, Chenyang Gao, Yulong Shen and Teng Li
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Yuelin Gao: Ningxia Province Key Laboratory of Intelligent Information and Data Processing, North Minzu University, Yinchuan 750021, China
Kaiguang Wang: Ningxia Province Key Laboratory of Intelligent Information and Data Processing, North Minzu University, Yinchuan 750021, China
Chenyang Gao: School of Cyber Engineering, Xidian University, Xi’an 710071, China
Yulong Shen: School of Cyber Engineering, Xidian University, Xi’an 710071, China
Teng Li: School of Cyber Engineering, Xidian University, Xi’an 710071, China

Mathematics, 2019, vol. 7, issue 12, 1-36

Abstract: There are some processing problems of imbalanced data such as imbalanced data sets being difficult to integrate efficiently. This paper proposes and constructs a mixed penalty function data integration screening criterion, and proposes Differential Evolution Integration Algorithm Based on Mixed Penalty Function Screening Criteria (DE-MPFSC algorithm). In addition, the theoretical validity and the convergence of the DE-MPFSC algorithm are analyzed and proven by establishing the Markov sequence and Markov evolution process model of the DE-MPFSC algorithm. In this paper, the entanglement degree and enanglement degree error are introduced to analyze the DE-MPFSC algorithm. Finally, the effectiveness and stability of the DE-MPFSC algorithm are verified by UCI machine learning datasets. The test results show that the DE-MPFSC algorithm can effectively improve the effectiveness and application of imbalanced data classification and integration, improve the internal classification of imbalanced data and improve the efficiency of data integration.

Keywords: imbalanced data; screening criteria; DE-MPFSC algorithm; Markov process; entanglement degree; data integration (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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