Discriminant ECOC: a heuristic method for application dependent design of error correcting output codes 论文

2006IEEE Transactions on Pattern Analysis and Machine Intelligence引用 260
Face and Expression RecognitionMachine Learning and AlgorithmsImbalanced Data Classification Techniques

摘要

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.