A multiclass classification method based on multiple pairwise classifiers
Tomoyuki Hamamura, Haruo Mizutani, Bunpei Irie · 2005
In this paper, a new method of composing a multiclass classifier using pairwise classifiers is proposed. A “Resemblance Model ” is exploited to calculate a posteriori probability for combining pairwise classifiers. We proved the validity of this model by using approximation of a posteriori probability formula. Using this theory, we can obtain the optimal decision. An experimental result of handwritten numeral recognition is presented, supporting the effectiveness of our method. 1.