Alternating multiconlitron: A novel framework for piecewise linear classification

作者：Li Yujian^*; Leng Qiangkui

来源：Pattern Recognition, 2015, 48(3): 968-975.

DOI：10.1016/j.patcog.2014.09.003

• Multiconlitron
• Alternating multiconlitron
• Maximal convexly separable subset
• Support alternating multiconlitron algorithm
• Piecewise linear classifier

Multiconlitron is a general framework for designing piecewise linear classifiers, but it may contain a relatively large number of conlitrons and linear functions. Based on the concept of maximal convexly separable subset (MCSS), we propose alternating multiconlitron as a novel framework for piecewise linear classification. Using the support alternating multiconlitron algorithm, an alternating multiconlitron can be constructed as a series of conlitrons alternately from a subset of one class to the MCSS of the other class. Experimental results show that in practice an alternating multiconlitron generally has a much simpler structure than a corresponding multiconlitron, performing very fast in testing phase with similar or better accuracies.

• 出版日期2015-3
• 单位北京工业大学