提出了基于统计学习的方法的电脑围棋程序。
Afterwards, the method based on the statistical learning was pointed out.
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.
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.
例如，我们的映射分析类似于从大的卫星图像数据或地理统计学习功能。
Our mapping analyses, for example, are similar to efforts to learn features from large satellite imagery data or geographic statistics.
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.
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.
因此，对统计学习模型的复杂性给出评价与选择的准则，一直是一个核心问题。
It has long been recognized that the Structural Risk Minimization (SRM) principle based on the concept of VC-dimension provides an excellent means for complexity selection of a learning machine.
由于现有自然语言处理技术以及统计学习技术的成熟，使浅层语义分析得以实现。
Because the technology of natural language processing and statistical learning is becoming more and more solid, it is possible to realize shallow semantic parsing.
通过对小样本数据的统计学习，能够推广到大规模数据中去进行结果的预测估计。
It could be generalized to test and estimate the big scale data by training the small sample.
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.
在探索手写字符识别的方法上采用了统计学习理论，利用支撑向量机SVM作为基本的识别工具。
Support Vector Machine (SVM) is used as the implementation basis, which is a tool of Statistical Learning Theory (SLT).
支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。
Support vector machines (SVM) are a kind of novel machine learning methods, based on statistical learning theory, which have been developed for solving classification and regression problems.
支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。
Support vector machines (SVM) are a kind of novel machine learning methods based on statistical learning theory, which has been developed to solve classification and regression problems.
如果有一个适当的相似性度量方法或一个结合图表形式的向量表示空间，统计学习技术则可以被用上。
Other statistical learning techniques are applied to these if given an appropriate proximity measure or a vectorial representation space found by graph embeddings [79].
支撑矢量机是根据统计学习理论提出的一种新的学习方法，即使用核函数在高维空间里进行有效的计算。
The support vector machine is a novel type of learning technique, based on statistical learning theory, which USES Mercer kernels for efficiently performing computations in high dimensional Spaces.
建立在统计学习理论基础之上的支持向量机(SVM)，是一种基于结构风险最小的小样本机器学习方法。
Support vector machine (SVM) is a novel and powerful learning method which is derived based on statistical learning theory (SLT) and the structural risk minimization principle.
建立在统计学习理论基础之上的支持向量机(SVM)，是一种基于结构风险最小的小样本机器学习方法。
Support vector machine (SVM) is a novel and powerful learning method which is derived based on statistical learning theory (SLT) and the structural risk minimization principle.
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