Книги з теми "Structured Support Vector Machine"

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

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

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

name, No. Least squares support vector machines. Singapore: World Scientific, 2002.

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

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

Bernhard, Schölkopf, Burges Christopher J. C, and Smola Alexander J, eds. Advances in kernel methods: Support vector learning. Cambridge, Mass: MIT Press, 1999.

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

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

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

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

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

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

Terzic, Jenny. Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications: A Support Vector Machine Approach. Heidelberg: Springer International Publishing, 2013.

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

Shi, 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.

Shi, 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.

-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.

Camps-Valls, Gustavo. Kernel methods for remote sensing 1: Data analysis 2. Hoboken, NJ: Wiley, 2009.

Steeb, W. H. The 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.

The 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.

Steeb, W. H. The 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.

The 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.

The 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.

International, 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.

Support Vector Machine In Chemistry. World Scientific Publishing Company, 2004.

Support Vector Machines. Springer New York, 2014.

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

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.

Suykens, Johan A. K., Marco Signoretto, and Andreas Argyriou. Regularization, Optimization, Kernels, and Support Vector Machines. Taylor & Francis Group, 2014.

Suykens, Johan A. K., Marco Signoretto, and Andreas Argyriou. Regularization Optimization Kernels and Support Vector Machines. Taylor & Francis Group, 2020.

Suykens, Johan A. K., Marco Signoretto, and Andreas Argyriou. Regularization, Optimization, Kernels, and Support Vector Machines. Taylor & Francis Group, 2014.

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.

Hamel, Lutz H. Knowledge Discovery with Support Vector Machines. Wiley & Sons, Incorporated, John, 2009.

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

(Editor), Bernhard Schölkopf, Christopher J. C. Burges (Editor), and Alexander J. Smola (Editor), eds. Advances in Kernel Methods: Support Vector Learning. The MIT Press, 1998.

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

Notebooks, Funny. I Support Vector Machine: 120 Pages I 6x9 I Lined. Independently Published, 2019.

Club, Rocket Baby. Toby's Best Wall : Machine Learning for Kids: Support Vector Machines. Primedia eLaunch LLC, 2019.

Notebooks, Funny. I Support Vector Machine: 120 Pages I 6x9 I Blank. Independently Published, 2019.

Notebooks, Funny. I Support Vector Machine: 120 Pages I 6x9 I Blank. Independently Published, 2019.

Notebooks, Funny. I Support Vector Machine: 120 Pages I 6x9 I Cornell Notes. Independently Published, 2019.

Notebooks, Funny. I Support Vector Machine: 120 Pages I 6x9 I Dot Grid. Independently Published, 2019.

Abe, Shigeo. Support Vector Machines for Pattern Classification (Advances in Pattern Recognition). Springer, 2005.

An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. Cambridge University Press, 2000.

Terzic, Edin, Jenny Terzic, Romesh Nagarajah, and Muhammad Alamgir. Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications: A Support Vector Machine Approach. Springer, 2015.

Terzic, Edin, Jenny Terzic, and Romesh Nagarajah. Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications: A Support Vector Machine Approach. Springer, 2013.

Support Vector Machine and Parametric Wavelet-Based Texture Classification of Stem Cell Images. Storming Media, 2004.