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Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines Theory, Algorithms and Applications /

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...

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Gorde:
Xehetasun bibliografikoak
Erakunde egilea: SpringerLink (Online service)
Beste egile batzuk: Rad, Jamal Amani (Argitaratzailea), Parand, Kourosh (Argitaratzailea), Chakraverty, Snehashish (Argitaratzailea)
Formatua: Baliabide elektronikoa eBook
Hizkuntza:ingelesa
Argitaratua: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Edizioa:1st ed. 2023.
Saila:Industrial and Applied Mathematics,
Gaiak:
Algebraic fields.
Polynomials.
Mathematical optimization.
Quantitative research.
Machine learning.
Pattern recognition systems.
Python (Computer program language).
Field Theory and Polynomials.
Optimization.
Data Analysis and Big Data.
Machine Learning.
Automated Pattern Recognition.
Python.
Sarrera elektronikoa:https://doi.org/10.1007/978-981-19-6553-1
Etiketak: Etiketa erantsi
Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!
Aurkibidea:
  • Introduction to SVM
  • Basics of SVM Method and Least Squares SVM
  • Fractional Chebyshev Kernel Functions: Theory and Application
  • Fractional Legendre Kernel Functions: Theory and Application
  • Fractional Gegenbauer Kernel Functions: Theory and Application
  • Fractional Jacobi Kernel Functions: Theory and Application
  • Solving Ordinary Differential Equations by LS-SVM
  • Solving Partial Differential Equations by LS-SVM
  • Solving Integral Equations by LS-SVR
  • Solving Distributed-Order Fractional Equations by LS-SVR
  • GPU Acceleration of LS-SVM, Based on Fractional Orthogonal Functions
  • Classification Using Orthogonal Kernel Functions: Tutorial on ORSVM Package.

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