支持向量机是一种基于统计学习理论的新型学习机。
The support vector machine (SVM) is a new learning machine based on the statistical learning theory.
基于统计学习理论的支持向量机便是一个典型的例子。
Support vector machines based on statistical learning theory is a typical example.
支持向量机是基于统计学习理论的一种新的机器学习方法。
Support Vector machine is a kind of new machine studying method, which is based on Statistical Learning Theory.
支持向量机是一种基于统计学习理论的新型机器学习方法。
Support vector machine (SVM) is a new learning machine based on the statistical learning theory.
基于统计学习理论的支持向量机是一种新型机器学习工具。
Support vector machines (SVM) based on the statistical learning theory is a new machine learning tool.
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.
在统计学习理论中，尤其对于分类问题，VC维扮演着中心作用。
VC dimension plays a central role in the Statistical Learning Theory especially for classification problems.
支持向量机(SVM)是基于统计学习理论的新一代机器学习技术。
Support vector machine (SVM) is a new generation machine learning technique based on the statistical learning theory.
支持向量机是基于统计学习理论框架下的一种简单、有效的分类方法。
Support Vector Machines algorithm is a simple and effective classification method based upon statistical learning theory.
基于支持向量机的直推式学习是统计学习理论中一个较新的研究领域。
Transductive inference based on support vector machine is a relatively new research region in statistical learning theory.
这个课程的重点将放在与统计学习理论架构中有关的监督式学习问题。
The course focuses on the problem of supervised learning within the framework of Statistical Learning Theory.
支持向量机是基于VC维和统计学习理论理念的数据挖掘中的一种新方法。
Support Vector Machine is a new method based on the idea of VC dimension and Statistical Learning Theory in data mining.
支持向量机是机器学习领域的研究热点之一，其理论基础是统计学习理论。
Support Vector machine is one of the hot points in machine learning research, it's theoretical basis is Statistical learning Theory.
支持向量机是机器学习领域的一个研究热点，它的理论基础是统计学习理论。
Support Vector Machine (SVM), based on the counts study theory, is a research hot spot in machine learning domain.
本文首次将统计学习理论及支持向量机方法引入提高采收率方法的潜力预测中。
In this paper, statistical learning theory and support vector machine method are introduced in eor potentiality prediction for the first time.
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.
介绍统计学习理论和支持向量机，提出利用支持向量机技术进行似大地水准面拟合。
This paper introduces statistical learning theory and support vector machine, proposes a new method, support vector machine technology, to simulate quasi-geoid.
与传统统计学相比，统计学习理论是一种专门研究小样本情况下机器学习规律的理论。
Compared with statistical theory, statistical learning theory focuses on the machine learning of small sample size and can trade off between the complexity of models and generalization performance.
基于统计学习理论中结构风险最小化原则的支持向量机是易于小样本的机器学习方法。
Support vector machine (SVM) based on the structural risk minimization of statistical learning theory is a method of machine learning for small sample set.
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.
支持向量机是统计学习理论的一个重要学习方法，也是解决模式识别问题的一个有力工具。
Support Vector Machine (SVM) is an important learning method of statistical learning theory, and is also a powerful tool for pattern recognition.
支持向量机是一种基于统计学习理论的机器学习算法，能够较好地解决小样本的学习问题。
As one algorithm of the machine learning based on the statistical learning theory, Support Vector machine (SVM) is specifically to the small samples learning case.
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.
支持向量机是统计学习理论的一个重要的学习方法，也是解抉模式识别问题的一个有力的工具。
Support vector machine (SVM) is an important learning method of statistical learning theory, and is also a powerful tool for pattern recognition problems.
支持向量机是一种基于统计学习理论的新型机器学习方法，它可以被广泛地用于非线性系统建模。
Support vector machine (SVM) is a brand-new machine learning technique based on statistical learning theory. It is an ideal facility for modeling of various nonlinear systems.
为了系统地归纳统计学习理论与支持向量机的基本思想和算法，总结目前该领域的最新研究成果。
The basic statistical learning theory (SLT) and its corresponding algorithms, support vector machines (SVMs), are surveyed, and especially, its latest research results are summarized and studied.
为了系统地归纳统计学习理论与支持向量机的基本思想和算法，总结目前该领域的最新研究成果。
The basic statistical learning theory (SLT) and its corresponding algorithms, support vector machines (SVMs), are surveyed, and especially, its latest research results are summarized and studied.
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