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Titlebook: Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines; Theory, Algorithms a Jamal Amani Rad,Kourosh Parand,Sneh

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书目名称Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines
副标题Theory, Algorithms a
编辑Jamal Amani Rad,Kourosh Parand,Snehashish Chakrave
视频videohttp://file.papertrans.cn/584/583023/583023.mp4
概述Introduces new fractional orthogonal kernels for support vector algorithms.Includes a Python package for utilizing the presented fractional orthogonal kernels.Contains examples that provide a deep int
丛书名称Industrial and Applied Mathematics
图书封面Titlebook: Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines; Theory, Algorithms a Jamal Amani Rad,Kourosh Parand,Sneh
描述.This book contains select chapters on support vector algorithms from different perspectives, including mathematical background, properties of various kernel functions, and several applications. The main focus of this book is on orthogonal kernel functions, and the properties of the classical kernel functions—Chebyshev, Legendre, Gegenbauer, and Jacobi—are reviewed in some chapters. Moreover, the fractional form of these kernel functions is introduced in the same chapters, and for ease of use for these kernel functions, a tutorial on a Python package named ORSVM is presented. The book also exhibits a variety of applications for support vector algorithms, and in addition to the classification, these algorithms along with the introduced kernel functions are utilized for solving ordinary, partial, integro, and fractional differential equations...On the other hand, nowadays, the real-time and big data applications of support vector algorithms are growing. Consequently, the Compute Unified Device Architecture (CUDA) parallelizing the procedure of support vector algorithms based on orthogonal kernel functions is presented. The book sheds light on how to use support vector algorithms base
出版日期Book 2023
关键词support vector machine; kernel; fractional; orthogonal function; pattern recognition
版次1
doihttps://doi.org/10.1007/978-981-19-6553-1
isbn_softcover978-981-19-6555-5
isbn_ebook978-981-19-6553-1Series ISSN 2364-6837 Series E-ISSN 2364-6845
issn_series 2364-6837
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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