Researching the Efficiency of Configurations of a Collective Decision-making System on the Basis of Fuzzy Logic

Polyakova, A S; Lipinskiy, Leonid; Semenkin, ‪Eugene

doi:10.5220/0009976602770285

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“…Hybridization of algorithms is one of these fields. Methods to designing neural networks, fuzzy logic systems, decision trees applying evolutionary algorithms are examples of such approaches (Khritonenko et al, 2017;Polyakova et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Hybridization of Machine Learning Models and Differential Evolution in Data Mining

Karaseva¹

2023

European Proceedings of Computers and Technology

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Nowadays, data mining methods are applied in various fields of science and technologies. The widespread application of these methods necessitates the development of procedures to improve the efficiency of basic methods. Often, the efficiency of approaches based on data mining methods significantly depends on the selection of numerical coefficients. Moreover, these numerical coefficients can be both parameters of the algorithm and parameters of the obtained solutions. Therefore, it is possible to apply optimization methods to determine the best values. Nowadays, one of the most efficient methods of real optimization is differential evolution. The paper presents the study the differential evolution application to optimize coefficients of a dynamic system model obtained by an approach based on a self-configuring genetic programming algorithm. Also, it considers optimization of threshold values for solving classification problems with decision trees. The paper considers the most popular methods for training decision trees. The selected tasks demonstrate the universality of the proposed modification, since they solve diverse tasks.Moreover, the applied data analysis methods belong to different classes. The results of numerical experiments are presented for these tasks. They prove efficiency of the proposed hybridization.

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Section: Introductionmentioning

confidence: 99%

Hybridization of Machine Learning Models and Differential Evolution in Data Mining

Karaseva¹

2023

European Proceedings of Computers and Technology

View full text Add to dashboard Cite

show abstract

Researching the Efficiency of Configurations of a Collective Decision-making System on the Basis of Fuzzy Logic

Cited by 1 publication

References 0 publications

Hybridization of Machine Learning Models and Differential Evolution in Data Mining

Hybridization of Machine Learning Models and Differential Evolution in Data Mining

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