Improved support vector machine algorithm for heterogeneous data

A support vector machine (SVM) is a popular algorithm for classification learning. The classical SVM effectively manages classification tasks defined by means of numerical attributes. However, both numerical and nominal attributes are used in practical tasks and the classical SVM does not fully cons...

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Veröffentlicht in:	Pattern recognition Jg. 48; H. 6; S. 2072 - 2083
Hauptverfasser:	Peng, Shili, Hu, Qinghua, Chen, Yinli, Dang, Jianwu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.06.2015
Schlagworte:	Classification learning Heterogeneous data Nominal attribute Numerical attribute Support vector machine Classification learning Nominal attribute Support vector machine Heterogeneous data Numerical attribute
ISSN:	0031-3203, 1873-5142
Online-Zugang:	Volltext
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