A Probabilistic Tri-class Support Vector Machine

A probabilistic interpretation for the output obtained from a tri-class Support Vector Ma-chine into a multi-classification problem is presented in this paper. Probabilistic outputs are defined when solving a multi-class problem by using an ensemble architecture with tri-class learning machines working in parallel. This architecture enables the definition of an ‘interpretation ’ mapping which works on signed and probabilistic outputs providing more control to the user on the classification problem