支持向量机（SVM）是建立在统计学习理论基础上的一种小样本机器学习方法，用于解决二分类问题。

Support Vector Machines(SVM) are developed from the theory of limited samples Statistical Learning Theory (SLT) by Vapnik et al. , which are originally designed for binary classification.

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目的解决二分类反应资料危险度指标区间估计问题。

Objective To solve the problem of estimation for risk data.

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本文研究基于凸风险最小化方法的多分类贪婪算法，推广二分类的学习问题到多分类的情形。

In this paper, learning algorithm for solving multi-category classification using convex upper losses is studied.

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