关键词: 组合凸线性感知器, SK算法, 通用框架, 分片线性分类器

Abstract: Multiconlitron is a general framework for constructing piecewise linear classifiers. This paper introduces a typical nearest point method, i.e. Schlesinger-Kozinec (SK) algorithm to compute the separating hyperplane between two convex polytopes for linearly separable data sets. By using SK algorithm, this paper constructs conlitron and multiconlitron to solve convexly separable and commonly separable problems, respectively. Experiments on both synthetic and real data sets show that the presented method has a good classification performance. Comparing with some other piecewise linear classifiers verifies the effectiveness of the presented method.

Key words: multiconlitron, SK algorithm, general framework, piecewise linear classifier