A Fast Multiclass Classification Algorithm Based on Cooperative Clustering

Authors:
Chuanhuan Yin;Xiang Zhao;Shaomin Mu;Shengfeng Tian
Affiliations:
School of Computer and Information Technology, Beijing Jiaotong University, Beijing, People's Republic of China;Datang International Power Generation Co., Ltd., Beijing, People's Republic of China;School of Computer and Information Engineering, Shandong Agriculture University, Taian, People's Republic of China;School of Computer and Information Technology, Beijing Jiaotong University, Beijing, People's Republic of China
Venue:
Neural Processing Letters
Year:
2013

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Abstract

We present a fast multiclass classification algorithm to address the multiclass problems with a new clustering method, namely cooperative clustering. In the method of cooperative clustering, we iteratively compute the cluster centers of all classes simultaneously. For every cluster center in a class, a cluster center in an adjacent class is selected and the pair of cluster centers is drawn towards the boundary. In this way, the data set around a class is found and the data set plus the data in this class can be trained to form a classifier. With cooperative clustering, one binary classifier in the one-vs-all approach can be trained with far less samples. Furthermore, a kNN method is proposed to accelerate the classifying procedure. With this algorithm, both training and classification efficiency are improved with a slight impact on classification accuracy.