Books on the topic 'Support Vector Machine Regression'

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

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

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.

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

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

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

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.

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

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. 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. 3rd ed. Hackensack, NJ: World Scientific, 2005.

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.

Sunteev, Anton. Management of internal reserves to reduce the cost of engineering products. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1141766.

O. Görgülü and A. Akilli. Egg production curve fitting using least square support vector machines and nonlinear regression analysis. Verlag Eugen Ulmer, 2018. http://dx.doi.org/10.1399/eps.2018.235.

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

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.

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

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

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.

(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.

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

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

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.

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

Support Vector Machines Chapman HallCRC Data Mining and Knowledge Discovery Serie. CRC Press, 2012.

Kernel Methods and Machine Learning. Cambridge University Press, 2014.

Wang, Lipo. Support Vector Machines: Theory and Applications (Studies in Fuzziness and Soft Computing). Springer, 2005.

Goldberg, Andrew, and Xiaojin Zhu. Introduction to Semi-supervised Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning). Morgan & Claypool Publishers, 2008.

Miao, Chuxiong, and Ming Zuo. A Support Vector Machine Model for Pipe Crack Size Classification: Reseach on SVM Classification. VDM Verlag Dr. Müller, 2010.

Schlkopf, Bernhard, and Alexander J. Smola. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning). The MIT Press, 2001.

Computational Intelligence and Its Applications: Evolutionary Computation, Fuzzy Logic, Neural Network and Support Vector Machine Techniques. Imperial College Press, 2012.

Joachims, Thorsten. Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms (The International Series in Engineering and Computer Science). Springer, 2002.

(Editor), Constantine Balanis, ed. Support Vector Machines for Antenna Array Processing and Electromagnetics (Synthesis Lectures on Computational Electromagnetics Lecture). Morgan & Claypool Publishers, 2007.

(Editor), Bartlomiej Beliczynski, Andrzej Dzielinski (Editor), Marcin Iwanowski (Editor), and Bernadete Ribeiro (Editor), eds. Adaptive and Natural Computing Algorithms: 8th International Conference, ICANNGA 2007, Warsaw, Poland, April 11-14, 2007, Proceedings, Part I (Lecture Notes in Computer Science). Springer, 2007.