Similarly, with machine learning algorithms, a common problem is over-fitting the data and essentially memorizing the training set rather than learning a more general classification technique.
同样，对于机器学习算法，一个通常的问题是过适合(原文为over -fitting，译者注)数据，以及主要记忆训练集，而不是学习过多的一般分类技术。
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.
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。
So I'd say machine learning is guided and inspired by the theoretical results you get from computational learning theory.
所以我想说，机器学习是引导和启发你从计算学习理论的理论结果。
The support vector machine(SVM) is a new learning technique based on the statistical learning theory.
支持向量机（SVM）是根据统计理论提出的一种新的学习算法。
With a teaching machine, the individual student is responsible for his own learning while in a class, the learning is controlled by the teacher.
有了教学机，每个学生就为他自己的学习负责，然而在课堂上，学习是由老师控制的。
In taking on the more intractable challenges, Google is looking to draw on deep learning, the most advanced form of machine learning.
为了应对更棘手的挑战，谷歌正在寻求利用深度学习——机器学习的最高级形式。
Support vector machine (SVM) is a new generation machine learning technique based on the statistical learning theory.
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 general learning machine, which analyzes the consistency of learning and speed of convergence from structure risk minimization principle.
支持向量机(SVM)是一种新的通用学习机器，它从结构风险最小化的角度，分析了学习过程的一致性、收敛速度等。
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。
Support vector machine (SVM) is a new learning machine based on the 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。
In this paper the concept of ability order of learning machine is introduced and a model of second order learning machine is given.
本文引入学习机的功能阶数的概念，给出二阶学习机的一种工作模型。
Lie group Machine learning (LML) inherit the advantages of manifold learning method and make full use of the Lie group's structure of algebraic and geometry in mathematics.
李群机器学习(LML)既继承了流形学习的优点，又充分利用了李群的代数结构和几何结构的数学本质，自提出以来就引起了许多研究者的关注。
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。
Decision tree learning strategy have long been popular in pattern recognition, machine learning, and other disciplines for solving problems concerned with the classification.
决策树学习策略广泛应用于模式识别和机器学习等领域，用来解决与分类相关的问题。
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。
Classification Learning is the important content in Machine Learning.
分类学习是机器学习重要的研究内容。
Ontology learning aims at the integration of a multitude of disciplines such as ontology engineering techniques and machine learning techniques to construct the ontology (semi) automatically.
本体学习技术是利用本体工程技术和机器学习技术等众多学科技术来实现本体的(半)自动构建。
SVM is a novel powerful machine learning method developed in the framework of Statistical Learning Theory (SLT).
支持向量机是在统计学习理论基础上开发出来的一种新的、非常有效的机器学习方法。
As this discussion makes clear, machine learning has a formidable learning curve, for which years of classroom and laboratory work at the university level may prove essential.
由于这种讨论表明，机器学习有着强大的学习曲线，因为在大学中几年的教室和实验室工作，可能被证明是必不可少的。
For example, you may write about the use of machine learning in natural language processing or review sample complexity of machine learning algorithms.
例如，你可以写关于在自然语言处理中使用机器学习的报告或机器学习中各算法的抽样复杂度的比较整理。
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.
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 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研究热点之一，其理论基础是统计学习理论。
Currently, Manifold learning gradually becomes a hotspot in the field of machine learning and pattern recognition.
月前，流形学习渐渐成为机器学习及模式识别领域中的一个研究热点。
At present, manifold learning has become a hot issue in the field of pattern recognition, machine learning and data mining.
目前，流形学习已成为模式识别、机器学习和数据挖掘领域的研究热点问题。
Conceptual learning is one of the main constituents in machine learning.
概念学习是机器学习中的一个主要内容。
Multi-instance learning (MIL) has been regarded by some international experts as a new learning framework parallel to the three traditional machine learning frameworks.
多示例学习被国际上一些专家认为是与传统的三大机器学习框架并列的一种新型学习框架。
Multi-instance learning (MIL) has been regarded by some international experts as a new learning framework parallel to the three traditional machine learning frameworks.
多示例学习被国际上一些专家认为是与传统的三大机器学习框架并列的一种新型学习框架。
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