The analytical work involves applying statistical inference and machine learning techniques.
其分析工作涉及到统计推断及机器学习技术的应用。
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.
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。
In this paper, statistical learning theory and support vector machine method are introduced in eor potentiality prediction for the first time.
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。
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.
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。
This paper introduces statistical learning theory and support vector machine, proposes a new method, support vector machine technology, to simulate quasi-geoid.
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。
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。
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。
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。
Recently, many researchers try to handle coreference resolution with statistical machine learning and gain some achievement.
近年来，许多学者尝试利用统计机器学习的方法来进行共指消解并取得了一定的进展。
Statistical machine learning for translation services is now widely researched and is also used by some other websites, like Google Translate.
让统计机器学做翻译服务，目前受到了广泛的研究，也在谷歌翻译（GoogleTranslate）等其他一些网站得到了运用。
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。
There will be some discussion of statistical pattern recognition, but less than in the past, because this perspective is now covered in 6.893 Machine Learning and Neural Networks.
将有一些比过去少的统计模式认知的讨论，因为这观点现在包含在6.893机械学习和神经网路课程中。
Support vector machine (SVM) is the best general machine learning theory developed from statistical learning theory, and suit to do prediction from small samples by learning.
本文采用统计学习理论，建立了基于最小二乘支持向量机的永磁操动机构动作时间预测模型。
The Support Vector machine (SVM) is a new machine learning method based on the statistical learning theory and it is very useful to solve nonlinear problems of short time series.
支持向量机(SVM)方法是基于统计学理论的一种新的机器学习方法，对解决小样本条件下的非线性问题非常有效。
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。
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