Modified marine predators algorithm for feature selection: case study metabolomics; Knowledge and Information Systems (KAIS); Vol. 64, iss. 1

Modified marine predators algorithm for feature selection: case study metabolomics; Knowledge and Information Systems (KAIS); Vol. 64, iss. 1

Detaylı Bibliyografya
Parent link:Knowledge and Information Systems (KAIS)
Vol. 64, iss. 1.— 2022.— [P. 261–287]
Müşterek Yazar: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники
Diğer Yazarlar: Mokhamed Elsaed (Mohamed Abd Elaziz) A. M. Akhmed Mokhamed, Ahmed A. E. Ewees, Yousri D. Dalia, Laith A. Abualigah, Al-qaness Mohammed A. A.
Özet:Title screen
Feature selection (FS) is a necessary process applied to reduce the high dimensionality of the dataset. It is utilized to obtain the most relevant information and reduce the computational efforts of the classification process. Recently, metaheuristics methods have been widely employed for various optimization problems, including FS. In the current study, we present an FS method based on a new modified version of the marine predators algorithm (MPA). In the developed MPASCA model, the sine–cosine algorithm (SCA) is utilized to improve the search ability, which works as a local search of the MPA. To evaluate the performance of the MPASCA algorithm, extensive experiments were carried out using 18 UCI datasets. More so, the metabolomics dataset is used to test the proposed method as a real-world application. Furthermore, we implemented extensive comparisons to several state-of-art methods to verify the efficiency of the MPASCA. The evaluation outcomes showed that the MPASCA has significant performance, and it outperforms the compared methods in terms of classification measures.
Режим доступа: по договору с организацией-держателем ресурса
Dil:İngilizce
Baskı/Yayın Bilgisi: 2022
Konular:
электронный ресурс
труды учёных ТПУ
feature selection
metaheuristics
marine predators algorithm (MPA)
sine-cosine algorithm (SCA)
metabolomics dataset
метаэвристика
Online Erişim:https://doi.org/10.1007/s10115-021-01641-w
Materyal Türü: Elektronik Kitap Bölümü
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=668716

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