Multiclass Posterior Probability Support Vector Machines

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

• Type: Journal
• Year: 2008
• Where: TNN
• Authors: Mehmet Gönen, Ayse Gönül Tanugur, Ethem Alpaydin
• Keywords: Density Estimator, Posterior, Tao Et Al, TNN 2008