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Feature Selection Using Different Transfer Functions for Binary Bat Algorithm

التفاصيل البيبلوغرافية
العنوان: Feature Selection Using Different Transfer Functions for Binary Bat Algorithm
المؤلفون: Omar Saber Qasim, Zakariya Y. Algamal
المصدر: International Journal of Mathematical, Engineering and Management Sciences, Vol 5, Iss 4, Pp 697-706 (2020)
بيانات النشر: Ram Arti Publishers, 2020.
سنة النشر: 2020
المجموعة: LCC:Technology
LCC:Mathematics
مصطلحات موضوعية: feature subset selection, bat algorithm, transfer function, metaheuristic algorithms, Technology, Mathematics, QA1-939
الوصف: The selection feature is an important and fundamental step in the preprocessing of many classification and machine learning problems. The feature selection (FS) method is used to reduce the amount of data used and to create high-probability of classification accuracy (CA) based on fewer features by deleting irrelevant data that often reason confusion for the classifiers. In this work, bat algorithm (BA), which is a new metaheuristic rule, is applied as a wrapper type of FS technique. Six different types of BA (BA-S and BA-V) are proposed, where apiece used a transfer function (TF) to map the solutions from continuous space to the discrete space. The results of the experiment show that the features that use the BA-V methods (that is, the V-shaped transfer function) have proven effective and efficient in selecting subsets of features with high classification accuracy.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2455-7749
Relation: https://www.ijmems.in/volumes/volume5/number4/56-IJMEMS-20-04-54-697-706-2020.pdf; https://doaj.org/toc/2455-7749
DOI: 10.33889/IJMEMS.2020.5.4.056
URL الوصول: https://doaj.org/article/bfc74fdc65264f12bce24c6bc4cb617b
رقم الأكسشن: edsdoj.bfc74fdc65264f12bce24c6bc4cb617b
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:24557749
DOI:10.33889/IJMEMS.2020.5.4.056