Produce an algorithm based on encoding binary tree and supporting vector multi-category classification algorithm.
给出了一种基于编码二叉树的支持向量的多类分类算法。
In this paper, learning algorithm for solving multi-category classification using convex upper losses is studied.
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。
Secondly, the text studies the Statistical Learning Theory(STL) and Support Vector Machine(SVM)theory seriously, discusses multi-category classification algorithms of SVM.
其次，认真研究了统计学习理论的主要内容和SVM算法的基本原理，并且就SVM的多种多类别分类算法分别加以讨论。
Directed acyclic graph support vector (DAG - SVMS) multi - category classification methods, is a new multi - category classification methods.
有向无环图支持向量(DAG-SVMS)多类分类方法，是一种新的多类分类方法。
Directed acyclic graph support vector (DAG - SVMS) multi - category classification methods, is a new multi - category classification methods.
有向无环图支持向量(DAG-SVMS)多类分类方法，是一种新的多类分类方法。
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