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Title of Journal: Int J Mach Learn Cyber

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Abbravation: International Journal of Machine Learning and Cybernetics

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Springer-Verlag

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DOI

10.1002/tera.1420150212

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1868-808X

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Separating theorem of samples in Banach space for

Authors: Qiang He Congxin Wu
Publish Date: 2011/03/10
Volume: 2, Issue: 1, Pages: 49-54
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Abstract

The theory of machine learning in Banach space is a new research topic and has drawn much attention in recent years The theoretical foundation of this topic is that under what conditions two sample sets can be separated in Banach space In this paper motivated by developing new support vector machine SVM in Banach space we present a necessary and sufficient condition of separating two finite classes of samples by a hyperplane in Banach space We also present an attainable expression of maximal margin of the separating hyperplanes which includes some cases of the classes of infinite samples in Banach spaceThis work is partly supported by National NSFCs 61070242 by the Natural Science Foundation of Hebei Province F2010000323 by the Scientific Research Project of Department of Education of Hebei Province 2009410 by Scientific Research Project of Hebei University 09265631D2 and by 2010 Baoding science Research and Development Project 10ZG008

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