采用类电磁机制算法的SVM决策树多分类策略

doi:10.3969/j.issn.1001-2400.2014.06.014

Abstract

Abstract:

Based on the characteristics of the classification problem, a modified electromagnetism-like mechanism (EM) algorithm is designed, which is suitable for classification. Then a modified EM-based optimal decision-tree algorithm is proposed to deal with the SVM multi-class classification problem. First, EM is used to create an optimal or near-optimal decision tree automatically, which makes the margin between two classes maximal at every decision node. Then at every decision node, standard SVM is used to make binary classification. Finally, the SVM decision tree achieves multi-classification. Experimental results show that the proposed method is better than the traditional methods such as “1-a-1”, “1-a-r”, “DAG-SVM”,“DT-SVM” and “GADT-SVM”.

Key words: electromagnetism-like mechanism algorithm, support vector machine, multi-classification, maximal margin, decision tree

CLC Number:

TP391

JIANG Jianguo;ZHAO Yuan;MENG Hongwei;LI Bo. SVM decision-tree multi-classification strategy via electromagnetism-like mechanism[J].J4, 2014, 41(6): 83-88.

References

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SVM decision-tree multi-classification strategy via electromagnetism-like mechanism

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