Multicategory Classification Based on the Hypercube Self-Organizing Mapping (SOM) Scheme
A new multicalss recognition strategy is proposed in this paper, where the self-organizing mapping (SOM) scheme with a hypercube mapped space is used to represent each category in a binary string format and a binary classifier is assigned to each bit in the string. Our strategy outperforms the existing approaches in the prior knowledge requirement, the number of binary classifiers, computation complexity, storage requirement, decision boundary complexity and recognition rate.
KeywordsRecognition Rate Cluster Center Decision Boundary Binary Classifier Test Calibration
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