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Can I read Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines : Theory, Algorithms and Applications on EtoBox?
Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines : Theory, Algorithms and Applications by Jamal Amani Rad (editor), Kourosh Parand (editor), Snehashish Chakraverty (editor) is a mathematics available to read on EtoBox.
What is Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines : Theory, Algorithms and Applications about?
<p>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
Who reads Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines : Theory, Algorithms and Applications?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Jamal Amani Rad (editor), Kourosh Parand (editor), Snehashish Chakraverty (editor)
- Publisher
- Springer Nature Singapore Pte Ltd Fka Springer Science + Business Media Singapore Pte Ltd
- Published
- 2023
- Language
- EN
- ISBN
- 9789811965524
- Category
- mathematics
- Subjects
- Management, Mathematics, Language Learning
- Updated
- 2026-03-25