Hierarchical support vector machines for multi-class pattern recognition

被引：0

作者：

Schwenker, Friedhelm ^{[1
]}

机构：

[1] Univ of Ulm, Ulm, Germany

来源：

International Conference on Knowledge-Based Intelligent Electronic Systems, Proceedings, KES | 2000年 / 2卷

关键词：

Learning algorithms - Learning systems - Statistical methods - Trees (mathematics);

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Support vector machines (SVM) are learning algorithms derived from statistical learning theory. The SVM approach was originally developed for binary classification problems. In this paper SVM architectures for multi-class classification problems are discussed, in particular we consider binary trees of SVMs to solve the multi-class problem. Numerical results for different classifiers on a benchmark data set of handwritten digits are presented.

引用

页码：561 / 565

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