Titlebook: Next Generation Information Processing System; Proceedings of ICCET Prachi Deshpande,Ajith Abraham,Kun Ma Conference proceedings 2021 Sprin

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Kamireddy Manohar,Vijayasri Bolisetti,Sanjeev Kumarhe work also discusses another popular linear classifier, the perceptron, and compares its performance with that of the SVM in different application areas.>.978-3-319-41062-3978-3-319-41063-0Series ISSN 2191-5768 Series E-ISSN 2191-5776

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Kuldeep Narayan Tripathi,Gourav Jain,Ashish Mohan Yadav,S. C. Sharmais to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety of applications. We try to achieve this by presenting the basic ideas of SVMs together with the latest developments and current research questions in a uni?ed style. In a nut

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Sumit Pundir,Mohammad Wazid,Ayan Bakshi,Devesh Pratap Singhis to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety of applications. We try to achieve this by presenting the basic ideas of SVMs together with the latest developments and current research questions in a uni?ed style. In a nut

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G. U. Mali,D. K. Gautamtreatment of state-of-the-art results on support vector machEvery mathematical discipline goes through three periods of development: the naive, the formal, and the critical. David Hilbert The goal of this book is to explain the principles that made support vector machines (SVMs) a successful modelin

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Severin Gbetondji Michoagan,S. M. Mali,Sharad Goreis to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety of applications. We try to achieve this by presenting the basic ideas of SVMs together with the latest developments and current research questions in a uni?ed style. In a nut

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Kanchan R. Mangrule,H. T. Ingale,S. K. Chaudhari,Anil J. Patiltreatment of state-of-the-art results on support vector machEvery mathematical discipline goes through three periods of development: the naive, the formal, and the critical. David Hilbert The goal of this book is to explain the principles that made support vector machines (SVMs) a successful modelin