本文对目前地下水环境质量预测的研究方法进行了系统总结，详细地阐述了统计学习理论研究的基本问题及主要内容。
In this thesis, the current groundwater quality prediction methods were systematically summarized and the essential issues and main contents of statistical learning theory are elaborated.
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。
Secondly, the text studies the Statistical Learning Theory(STL) and Support Vector Machine(SVM)theory seriously, discusses multi-category classification algorithms of SVM.
首先概述了本文研究内容的基础—统计学习理论与支持向量机方法，为本文后续的研究方向和内容进行了铺垫。
This paper's basic concepts of Statistical Learning Theory and SVM are summarized firstly, which are the groundwork of next research works.
本文在经典统计学习理论的基础上，讨论了可能性空间上学习过程一致收敛速度的界。
In this paper, the bounds on the rate of uniform convergence of the learning processes on possibility space are discussed based on the classic Statistical learning Theory.
本项目以统计学习理论为基础，深入研究了应用支持向量机方法解决机械智能诊断和状态预测的相关问题。
Based on statistical learning theory (SLT), the relevant problems of solving the machinery intelligent diagnosis and condition prediction are thoroughly researched in this project by means of SVM.
在分类器的设计上，重点讨论了最近邻分类器和基于统计学习理论的支持向量机(SVM)。
We emphases discussed the nearest neighbor classifier and support vector machine (SVM) based on the statistical study theory.
支持向量机是一种基于统计学习理论的机器学习方法，它解决了神经网络中存在的一系列问题。
Support Vector Machine(SVM) is a machine learning method based on Statistical Learning Theory. It can solve a series of issues of Neural Networks.
统计学习理论具有坚实的理论基础，为解决小样本学习问题提供了统一的框架。
Statistical Learning Theory is based on a solid theoretical foundation. It provides an unified framework for solving the small sample learning problem.
在对统计学习理论以及相关的优化理论进行回顾的基础上，从四个方面详细描述了SVR模型的基础知识，并指出了SVM的优缺点。
With an overview on the statistical learning theory and the related optimization theory, we expound the basic knowledge of SVR model and point out the advantages and disadvantages of SVM.
文章系统地介绍了支持向量机和其理论基础——统计学习理论。
This paper studies SVM and its theory basic-statistical learning theory.
文章系统地介绍了支持向量机和其理论基础——统计学习理论。
This paper studies SVM and its theory basic-statistical learning theory.
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