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。
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。
Recently statistical machine learning methods have been substantially attempted for this issue with some achievements.
在最大熵等统计机器学习模型当中，特征函数的选择可以说是对系统整体性能影响最大的部分。
The feature functions were reckoned as the most important part of the maximum entropy model which could affact the last result of system.
温斯顿说：“机器学习往往提供更可靠的统计形式，使数据更有价值。”
"Machine learning often provides a more reliable form of statistics which makes data more valuable," says Winston.
因此，在传统的数学和物理基础课题之外，应该增加一门融合了计算机科学、编程、统计学和机器学习的新学科。
Therefore, a new discipline blending computer science, programming, statistics and machine learning should be added to the traditional foundational topics of mathematics and physics.
其分析工作涉及到统计推断及机器学习技术的应用。
The analytical work involves applying statistical inference and machine learning techniques.
目前，离群挖掘正逐渐成为数据库、机器学习、统计学等领域研究人员的研究热点。
At present, outlier data mining is a hotspot for the researchers of database, machine learning and statistics.
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.
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.
支持向量机是一种基于统计理论的机器学习算法，在解决小样本、非线性及高维模式识别中有独特的优势。
Support vector machine is a kind of machine study algorithm based on statistic theory, it has special advantage in solving small sample, non-linear and high dimension mode recognition.
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.
通过模糊统计的方法，将模糊知识进行量化，达到机器学习的目的。
By using the method of fuzzy statistics, fuzzy knowledge can be quantified to achieve the purpose of machine learning.
从建立已久的统计方法到更新近的机器学习技术，这本书提供这些重要的数据分析方法的概述。
This book provides an overview of these important data analysis methods, from long-established statistical methods to more recent machine learning techniques.
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.
数据挖掘是一门交叉性学科，涉及机器学习、模式识别、归纳推理、统计学、数据库、高性能计算等多个领域。
Data mining is an intercrossed subject, involving many fields such as machine learning, model reorganization, induction and deduction, statistics, database and high performance calculation.
KDD是一门新兴的交叉学科，主要涉及机器学习、统计学、数据库、专家系统以及数据可视化等多个学科领域。
KDD is a newly emerging and multi-disciplinary field of research; machine learning, statistics, database technology, expert systems and data visualization all make a contribution.
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.
机器学习是计算机科学与统计学的自然交集。
Machine Learning is a natural outgrowth of the intersection of Computer Science and Statistics.
数据挖掘是近年来出现的一种综合了机器学习、统计学、数据库等众多领域的新技术。
Data Mining is a new technology which appeared in recent years. It combines with machine learning, statistics, database and many other fields' technologies.
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.
基于统计学习理论的支持向量机是一类新型的机器学习算法，由于它出色的学习性能，该技术已经成为当前学术界的研究热点。
The support vector machine based on statistical learning is a new type of machine learning algorithm, which has become the hot spot of academic study because of its excellent learning performance.
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.
支持向量机是一种基于统计学习理论的机器学习方法，该理论主要研究在有限样本下的学习问题。
Support vector machine is a kind of machine learning algorithm based on statistical learning theory which mainly researches the learning of limited number of samples.
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.
数据挖掘是个新兴的研究领域，涉及到统计学、数据库、机器学习等众多学科，正以其强大的功能和广泛的应用受到高度的关注。
DataMing is a new study realm, coming down to many subjects such as statistics, database, machine learning and so on, it was paid high attention for its strong functions and broad application.
数据挖掘是个新兴的研究领域，涉及到统计学、数据库、机器学习等众多学科，正以其强大的功能和广泛的应用受到高度的关注。
DataMing is a new study realm, coming down to many subjects such as statistics, database, machine learning and so on, it was paid high attention for its strong functions and broad application.
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