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TNN
2008

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Multiclass Posterior Probability Support Vector Machines

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Multiclass Posterior Probability Support Vector Machines

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Abstract--Tao et al. have recently proposed the posterior probability support vector machine (PPSVM) which uses soft labels derived from estimated posterior probabilities to be more robust to noise and outliers. Tao et al.'s model uses a window-based density estimator to calculate the posterior probabilities and is a binary classifier. We propose a neighbor-based density estimator and also extend the model to the multiclass case. Our bias

Mehmet Gönen, Ayse Gönül Tanugur, E

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Density Estimator | Posterior | Tao Et Al | TNN 2008 |

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Added	15 Dec 2010
Updated	15 Dec 2010
Type	Journal
Year	2008
Where	TNN
Authors	Mehmet Gönen, Ayse Gönül Tanugur, Ethem Alpaydin

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