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Support Vector Machines: Data Analysis, Machine Learning, and Applications

• Authors : Boyle, Brandon H.

Subjects: Support vector machinesCOMPUTERS / Optical Data Processing

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Support Vector Machines to Propose a Ground Motion Prediction Equation for the Particular Case of the Bojorquez Intensity Measure I Np.

• Authors : Bojórquez, Edén¹ (AUTHOR); Payán-Serrano, Omar² (AUTHOR) ; Bojórquez, Juan^1,3 (AUTHOR)

• Source: AI. Oct2025, Vol. 6 Issue 10, p254. 20p.

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Modified Soft Margin Optimal Hyperplane Algorithm for Support Vector Machines Applied to Fault Patterns and Disease Diagnosis.

• Authors : Ruz Canul, Mario Antonio¹ (AUTHOR); Ruz-Hernandez, Jose A.² (AUTHOR) ; Alanis, Alma Y.¹ (AUTHOR)

• Source: Symmetry (20738994). Oct2025, Vol. 17 Issue 10, p1749. 40p.

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Support vector machines for optimal channel decoding.

• Authors : De Boni Rovella, Gastón^1,2 (AUTHOR) ; Benammar, Meryem³ (AUTHOR) ; Benaddi, Tarik⁴ (AUTHOR)

• Source: EURASIP Journal on Wireless Communications & Networking. 8/27/2025, Vol. 2025 Issue 1, p1-22. 22p.

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Fluorescence Guided Raman Spectroscopy enables the training of robust support vector machines for the detection of tumour marker proteins.

• Authors : Reifenrath, Johannes¹ (AUTHOR) ; Gardner, Benjamin² (AUTHOR); Gigler, Alexander^3,4 (AUTHOR)

• Source: Scientific Reports. 7/3/2025, Vol. 15 Issue 1, p1-14. 14p.

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Personalized Assistance with Support Vector Machines and Iot for Smart Operating Rooms.

• Authors : Mahil, J.¹ ; Jones, C. Berin² ; Paul, Vince³

• Source: Journal of Neonatal Surgery. 2025 Supplement, Vol. 14, p618-626. 9p.

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Multi-Task Learning Based on Support Vector Machines and Twin Support Vector Machines: A Comprehensive Survey

• Authors : Bazikar, Fatemeh; Moosaei, Hossein; Hemmati, Atefeh

Subjects: Machine Learning; Optimization and Control

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Improvement of support vector machines for mixed VOCs gas recognition based on an arithmetic optimization algorithm.

• Authors : LI, Cong¹; CHANG, XueTing¹; DAI, ChangQian²

• Source: Journal of Beijing University of Chemical Technology (Natural Science Edition) / Beijing Huagong Daxue Xuebao (Ziran Kexueban). Jul2025, Vol. 52 Issue 4, p138-146. 9p.

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Application of Support Vector Machines Kernel Functions for Breast Cancer Detection and Classification: A Comparative Study.

• Authors : Salih, Raz M. Hama¹ ; Mahmood, Saman H.¹

Subjects: *Support vector machines; *Radial basis functions; *Tumor classification

• Source: Cihan University-Erbil Scientific Journal. 2025, Vol. 9 Issue 1, p41-46. 6p.

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Quantum kernel and HHL-based support vector machines for multi-class classification

• Authors : Pinheiro, Gabriela; Slabbert, Donovan; Kowada, Luis

Subjects: Quantum Physics

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