Books on the topic 'Support vector machines'

Andreas, Christmann, ed. Support vector machines. New York: Springer, 2008.

Campbell, Colin. Learning with support vector machines. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool, 2011.

Support vector machines applications. Cham [Switzerland]: Springer, 2014.

Jayadeva, 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.

Ma, 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.

Joachim, Diederich, ed. Rule extraction from support vector machines. Berlin: Springer, 2008.

Campbell, 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.

Murty, 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.

missing], [name. Least squares support vector machines. Singapore: World Scientific, 2002.

Hamel, Lutz. Knowledge discovery with support vector machines. Hoboken, N.J: John Wiley & Sons, 2009.

Support vector machines for pattern classification. 2nd ed. London: Springer, 2010.

Lee, 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.

Abe, Shigeo. Support Vector Machines for Pattern Classification. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-098-4.

Wang, Lipo, ed. Support Vector Machines: Theory and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b95439.

Diederich, 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.

Drezet, P. Support vector machines for system identification. Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1998.

Boyle, Brandon H. Support vector machines: Data analysis, machine learning, and applications. Hauppauge, N.Y: Nova Science Publishers, 2011.

National 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.

K, Suykens Johan A., Signoretto Marco, and Argyriou Andreas, eds. Regularization, optimization, kernels, and support vector machines. Boca Raton: Taylor & Francis, 2014.

Ertekin, Şeyda. Algorithms for efficient learning systems: Online and active learning approaches. Saarbrücken: VDM Verlag Dr. Müller, 2009.

Joachims, Thorsten. Learning to classify text using support vector machines. Boston: Kluwer Academic Publishers, 2002.

Joachims, 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.

Stoean, 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.

Joachims, Thorsten. Learning to Classify Text Using Support Vector Machines. Boston, MA: Springer US, 2002.

Martinez-Ramon, Manuel. Support vector machines for antenna array processing and electromagnetics. [San Rafael, Calif.]: Morgan & Claypool Publishers, 2006.

Martínez-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.

Drezet, P. Directly optimized support vector machines for classification and regression. Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1998.

J, Smola Alexander, ed. Learning with kernels: Support vector machines, regularization, optimization, and beyond. Cambridge, Mass: MIT Press, 2002.

Support vector machines and their application in chemistry and biotechnology. Boca Raton: CRC Press, 2011.

Rad, Jamal Amani, Kourosh Parand, and Snehashish Chakraverty, eds. Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6553-1.

Lean, Yu, ed. Bio-inspired credit risk analysis: Computational intelligence with support vector machines. Berlin: Springer Verlag, 2008.

-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.

Léon-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.

Lorenzo, Bruzzone, ed. Kernel methods for remote sensing 1: Data analysis 2. Hoboken, NJ: Wiley, 2009.

Rezaul, Begg, and Palaniswami Marimuthu, eds. Computational intelligence for movement sciences: Neural networks, support vector machines, and other emerging technologies. Hershey, PA: Idea Group Pub., 2006.

Support Vector Machines. Springer New York, 2014.

Support Vector Machines. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-77242-4.

Ma, Yunqian, and Guodong Guo. Support Vector Machines Applications. Springer, 2016.

Diederich, Joachim. Rule Extraction from Support Vector Machines. Springer, 2010.

Least squares support vector machines. River Edge, NJ: World Scientific, 2002.

Pigozzi, Colin, and Yiming Genesereth. Learning with Support Vector Machines. Springer International Publishing AG, 2011.

Vandewalle, 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.

Wang, Lipo. Support Vector Machines: Theory and Applications. Springer Berlin / Heidelberg, 2010.

Support Vector Machines for Pattern Classification. London: Springer-Verlag, 2005. http://dx.doi.org/10.1007/1-84628-219-5.

Saigal, Pooja. Support-Vector Machines: History and Applications. Nova Science Publishers, Incorporated, 2020.

Hamel, Lutz H. Knowledge Discovery with Support Vector Machines. Wiley & Sons, Incorporated, John, 2011.

Hamel, Lutz H. Knowledge Discovery with Support Vector Machines. Wiley & Sons, Incorporated, John, 2011.

Abe, Shigeo. Support Vector Machines for Pattern Classification. Springer London, Limited, 2005.

Abe, Shigeo. Support Vector Machines for Pattern Classification. Springer, 2010.

Abe, Shigeo. Support Vector Machines for Pattern Classification. Springer London, Limited, 2012.