A comparative study on large scale kernelized support vector machines
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DOI: 10.1007/s11634-016-0265-7
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- Bischl, Bernd & Lang, Michel & Mersmann, Olaf & Rahnenführer, Jörg & Weihs, Claus, 2015. "BatchJobs and BatchExperiments: Abstraction Mechanisms for Using R in Batch Environments," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i11).
- Joachims, Thorsten, 1998. "Making large-scale SVM learning practical," Technical Reports 1998,28, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
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- Behzad Pirouz & Behrouz Pirouz, 2023. "Multi-Objective Models for Sparse Optimization in Linear Support Vector Machine Classification," Mathematics, MDPI, vol. 11(17), pages 1-18, August.
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Keywords
Support vector machine; Multi-objective optimization; Supervised learning; Machine learning; Large scale; Nonlinear SVM; Parameter tuning;All these keywords.
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