第4章，支持向量机的部分进展。
支持向量机是一种新的机器学习方法。
支持向量机是一种新的机器学习方法。
Support vector machine is a new kind of machine learning method.
支持向量机的模型选择研究。
支持向量机由核函数与训练集完全刻画。
It is completely characterized by kernel function and training set.
研究支持向量机在大类别数分类中的应用。
Support vector machine is a highly performance classification method.
模型选择是支持向量机一个重要的研究方向。
本文研究了支持向量机及其在概念设计中的应用。
In this paper, we presented support vector machine and applications in concept design.
支持向量机(SVM)是一种新的机器学习机制。
Support vector machine (SVM) is a new mechanism of machine learning.
回归型支持向量机方法SVR具有很好的学习性能。
Support Vector Machine for regression (SVR) has shown very good learning performance.
支持向量机不能直接对大规模的训练数据进行学习。
本文提出对手写相似汉字进行识别的支持向量机方法。
This paper presents a recognition method of similar Chinese handwriting by support vector machine.
文章中讨论支持向量机与基础追踪去杂讯法之间的关系。
This is the paper in which the relation between SVM and BPD is studied.
介绍了最小二乘支持向量机计算法和滑动时间窗的建立。
The establishment of beast square support vector machine method and sliding time window is introduced.
支持向量机是目前蛋白质远程同源检测应用最成功的方法。
Support Vector Machine is the most successful method of protein homology remote detection.
近年来，支持向量机(SVM)已成为统计学习理论的研究热点。
In recent years, Support Vector Machine (SVM) has become the research focus in statistical theory.
支持向量回归机是求解回归问题的新的十分有效的方法。
The support vector machine (SVM) is a very effective method for regression issue.
支持向量回归机是求解回归问题的新的十分有效的方法。
The support vector machine (SVM) is a very effective method for regression issue.
应用推荐