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Support-Vector Networks

Corinna Cortes^a, Vladimir N. Vapnik^a

^aAT&T Bell Labs., 07733, Holmdel, NJ, USA

Machine Learning Springer Science+Business Media1995-09-01 59K citations14 references

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TL;DRHigh generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated and the performance of the support- vector network is compared to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition. (Semantic Scholar)

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Support-Vector Networks

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