Books on the topic 'Support Vector Machine'
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Andreas, Christmann, ed. Support vector machines. New York: Springer, 2008.
Find full textCampbell, Colin. Learning with support vector machines. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool, 2011.
Find full textJoachim, Diederich, ed. Rule extraction from support vector machines. Berlin: Springer, 2008.
Find full textBoyle, Brandon H. Support vector machines: Data analysis, machine learning, and applications. Hauppauge, N.Y: Nova Science Publishers, 2011.
Find full textHamel, Lutz. Knowledge discovery with support vector machines. Hoboken, N.J: John Wiley & Sons, 2009.
Find full textmissing], [name. Least squares support vector machines. Singapore: World Scientific, 2002.
Find full textErtekin, Şeyda. Algorithms for efficient learning systems: Online and active learning approaches. Saarbrücken: VDM Verlag Dr. Müller, 2009.
Find full textSupport vector machines for pattern classification. 2nd ed. London: Springer, 2010.
Find full textJoachims, Thorsten. Learning to classify text using support vector machines. Boston: Kluwer Academic Publishers, 2002.
Find full textK, Suykens Johan A., Signoretto Marco, and Argyriou Andreas, eds. Regularization, optimization, kernels, and support vector machines. Boca Raton: Taylor & Francis, 2014.
Find full textBernhard, Schölkopf, Burges Christopher J. C, and Smola Alexander J, eds. Advances in kernel methods: Support vector learning. Cambridge, Mass: MIT Press, 1999.
Find full textJ, Smola Alexander, ed. Learning with kernels: Support vector machines, regularization, optimization, and beyond. Cambridge, Mass: MIT Press, 2002.
Find full text-W, Lee S., and Verri Alessandro, eds. Pattern recognition with support vector machines: First international workshop, SVM 2002, Niagara Falls, Canada, August 202 : proceedings. Berlin: Springer, 2002.
Find full textMartinez-Ramon, Manuel. Support vector machines for antenna array processing and electromagnetics. [San Rafael, Calif.]: Morgan & Claypool Publishers, 2006.
Find full textTerzic, Jenny. Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications: A Support Vector Machine Approach. Heidelberg: Springer International Publishing, 2013.
Find full textLéon-Charles, Tranchevent, Moor Bart, Moreau Yves, and SpringerLink (Online service), eds. Kernel-based Data Fusion for Machine Learning: Methods and Applications in Bioinformatics and Text Mining. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011.
Find full textLorenzo, Bruzzone, ed. Kernel methods for remote sensing 1: Data analysis 2. Hoboken, NJ: Wiley, 2009.
Find full textShi, Feng. Learn About Support Vector Machine in R With Data From the Adult Census Income Dataset (1996). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526495471.
Full textShi, Feng. Learn About Support Vector Machine in Python With Data From the Adult Census Income Dataset (1996). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526499585.
Full textSupport vector machines applications. Cham [Switzerland]: Springer, 2014.
Find full textJayadeva, Reshma Khemchandani, and Suresh Chandra. Twin Support Vector Machines. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-46186-1.
Full textMa, Yunqian, and Guodong Guo, eds. Support Vector Machines Applications. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02300-7.
Full textCampbell, Colin, and Yiming Ying. Learning with Support Vector Machines. Cham: Springer International Publishing, 2011. http://dx.doi.org/10.1007/978-3-031-01552-6.
Full textMurty, M. N., and Rashmi Raghava. Support Vector Machines and Perceptrons. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41063-0.
Full textLee, Seong-Whan, and Alessandro Verri, eds. Pattern Recognition with Support Vector Machines. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45665-1.
Full textAbe, Shigeo. Support Vector Machines for Pattern Classification. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-098-4.
Full textWang, Lipo, ed. Support Vector Machines: Theory and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b95439.
Full textDiederich, Joachim, ed. Rule Extraction from Support Vector Machines. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-75390-2.
Full textDrezet, P. Support vector machines for system identification. Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1998.
Find full textThe nonlinear workbook: Chaos, fractals, cellular automata, genetic algorithms, gene expression programming, support vector machine, wavelets, hidden Markov models, fuzzy logic with C++, Java and symbolic C++ programs. 6th ed. Hackensack, New Jersey: World Scientific, 2015.
Find full textNational Institute of Standards and Technology (U.S.), ed. Support vector machines applied to face recognition. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1998.
Find full textThe nonlinear workbook: Chaos, fractals, cellular automata, neural networks, genetic algorithms, gene expression programming, support vector machine, wavelets, hidden Markov models, Fuzzy logic with C++, Java and SymbolicC++ programs. 5th ed. New Jersey: World Scientific, 2011.
Find full textThe nonlinear workbook: Chaos, fractals, cellular automata, neural networks, genetic algorithms, gene expression programming, support vector machine, wavelets, hidden Markov models, Fuzzy logic with C++, Java and SymbolicC++ programs. 3rd ed. Hackensack, NJ: World Scientific, 2005.
Find full textThe nonlinear workbook: Chaos, fractals, cellular automata, neural networks, genetic algorithms, gene expression programming, support vector machine, wavelets, hidden Markov models, Fuzzy logic with C++, Java and SymbolicC++ programs. 5th ed. New Jersey: World Scientific, 2011.
Find full textThe nonlinear workbook: Chaos, fractals, cellular automata, neural networks, genetic algorithms, gene expression programming, support vector machine, wavelets, hidden Markov models, Fuzzy logic with C++, Java and SymbolicC++ programs. 4th ed. New Jersey: World Scientific, 2008.
Find full textJoachims, Thorsten. Learning to Classify Text Using Support Vector Machines. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0907-3.
Full textStoean, Catalin, and Ruxandra Stoean. Support Vector Machines and Evolutionary Algorithms for Classification. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06941-8.
Full textJoachims, Thorsten. Learning to Classify Text Using Support Vector Machines. Boston, MA: Springer US, 2002.
Find full textInternational, Conference on Artificial Neural Networks and Genetic Algorithms (2007 Warsaw Poland). Adaptive and natural computing algorithms: 8th international conference, ICANNGA 2007, Warsaw, Poland, April 11-14, 2007 : proceedings. Berlin: Springer, 2007.
Find full textMartínez-Ramón, Manel, and Christos Christodoulou. Support Vector Machines for Antenna Array Processing and Electromagnetics. Cham: Springer International Publishing, 2006. http://dx.doi.org/10.1007/978-3-031-01692-9.
Full textDrezet, P. Directly optimized support vector machines for classification and regression. Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1998.
Find full textSupport Vector Machines. Springer New York, 2014.
Find full textMa, Yunqian, and Guodong Guo. Support Vector Machines Applications. Springer, 2016.
Find full textSupport Vector Machine In Chemistry. World Scientific Publishing Company, 2004.
Find full textDiederich, Joachim. Rule Extraction from Support Vector Machines. Springer, 2010.
Find full textLeast squares support vector machines. River Edge, NJ: World Scientific, 2002.
Find full textVandewalle, Joos, Bart De Moor, Tony Van Gestel, Jos De Brabanter, and Johan A. K. Suykens. Least Squares Support Vector Machines. World Scientific Publishing Company, 2003.
Find full textWang, Lipo. Support Vector Machines: Theory and Applications. Springer Berlin / Heidelberg, 2010.
Find full textSuykens, Johan A. K., Marco Signoretto, and Andreas Argyriou. Regularization, Optimization, Kernels, and Support Vector Machines. Taylor & Francis Group, 2014.
Find full textSuykens, Johan A. K., Marco Signoretto, and Andreas Argyriou. Regularization, Optimization, Kernels, and Support Vector Machines. Taylor & Francis Group, 2014.
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