A probabilistic interpretation for the output obtained from a tri-class Support Vector Machine
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.
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CitationGonzález, L. [et al.]. A probabilistic tri-class Support Vector Machine. "Journal of pattern recognition research", Juliol 2010, vol. 5, núm. 1, p. 1-9.
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