Abstract
Support vector machines have established themselves as a standard data mining and machine learning tool. It is based on advances in statistical learning theory and finds a wide range of application in real-world situations like text categorization, handwritten character recognition, image classification, bio-sequences analysis, etc. The original SVM algorithm was invented by ‘Vladimir N. Vapnik’, and the current standard incarnation (soft margin) was proposed by ‘Vapnik and Corinna Cortes’ in 1995.
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References
Burges CJC (1998) A tutorial on support vector machines for pattern recognition. Data Min Knowl Disc 2(2):121–167
Vapnik V (1998) Statistical learning theory. Springer, New York
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Mohapatra, S., Ganesh, K., Punniyamoorthy, M., Susmitha, R. (2018). Developing a Classification Model Using SVM. In: Service Quality in Indian Hospitals. Advances in Theory and Practice of Emerging Markets. Springer, Cham. https://doi.org/10.1007/978-3-319-67888-7_8
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DOI: https://doi.org/10.1007/978-3-319-67888-7_8
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