Discriminant ECOC: a heuristic method for application dependent design of error correcting output codes.
We present a heuristic method for learning error correcting output codes matrices based on a hierarchical partition of the class space that maximizes a discriminative criterion. To achieve this goal, the optimal codeword separation is sacrificed in favor of a maximum class discrimination in the partitions. The creation of the hierarchical partition set is performed using a binary tree. As a result, a compact matrix with high discrimination power is obtained. Our method is validated using the UCI database and applied to a real problem, the classification of traffic sign images.
Pujol
Oriol
O
Departament de Matemática Aplicada i Análisi, Universitat de Barcelona, Gran Via 585, Barcelona, 08007, Spain. oriol@maia.ub.es
Radeva
Petia
P
Vitrià
Jordi
J
D000465:Algorithms; D001185:Artificial Intelligence; D016002:Discriminant Analysis; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*