该文对用于回归估计的标准支持向量机(SVM)加以改进，提出了一种新的用于回归估计的支持向量机学习算法。
Based on the traditional support vector machine (SVM) for regression, a new learning algorithm of the improved SVM for regression is presented in this paper.
支持向量机（SVM）是根据统计理论提出的一种新的学习算法。
The support vector machine(SVM) is a new learning technique based on the statistical learning theory.
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.
给出了使用多支持向量机进行增量学习的算法。
An incremental learning algorithm using multiple support vector machines (SVMs) is proposed.
为了提高性别检测的精度，提出了一种支持向量机(SVM)与主动外观模型(aam)相结合的迭代学习算法。
In order to increase accuracy in gender classification, an iterative learning approach combining support vector machine (SVM) and active appearance model (AAM) was proposed.
近年来，支持向量机算法被广泛地用于检索函数(排位函数)学习问题上且应用性能卓越。
In recent years, support vector machine algorithm is widely used on the issue of learning of retrieval function (ranking function) and performs excellently.
支持向量机(SVM)是一种基于结构风险最小化原理，具有很好推广性能的学习算法。
The support vector machine (SVM) is an algorithm based on structure risk minimizing principle and high generalization ability.
总结归纳了机器学习方法在目前生物信息学的应用，并对支撑向量机（SVM）算法的基本原理做了阐述；
Secondly, summarize the application of the machine learning methods in the bioinformatics and expatiate on the rationale of the Support Vector Machine (SVM).
为了将一般增量学习算法扩展到并行计算环境中，提出一种基于多支持向量机分类器的增量学习算法。
In order to extend common incremental learning algorithms into a parallel computation setting, an incremental learning algorithm with multiple support vector machine classifiers is proposed.
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.
本算法在保证分类准确度的同时，在增量学习问题上比传统的支持向量机有效。
This algorithm, in the incremental study question, is more effective than the traditional support vector machine, with assuring the classify accuracy.
提出了一种新的基于壳向量的增量式支持向量机快速学习算法。
A new geometric fast incremental learning algorithm for support vector machines (SVM) was proposed.
摘要：支持向量机(SVM)算法是统计学习理论中最年轻的分支。
Absrtact: SVM (support vector machine) algorithm is the newest branch of statistic learning theory.
对大规模训练样本的支持向量机训练问题进行探索，提出了一种基于正交表的并行学习算法。
Explores the training problems of support vector machine with large training pattern set, and a new parallel algorithm based on orthogonal array is presented.
本文主要致力于支持向量机、近似支持向量机的学习算法研究，特征提取的数学模型与算法的改进及其应用，聚类分析算法的收敛性证明。
This paper's main works is that: learning algorithm studies of support vector machine, mathematical model and application about feature selection, convergence analysis of clustering algorithm.
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.
支持向量机是一种机器学习算法，在国外已广泛应用于工程实践领域。
Support Vector Machines(SVMs)is an algorithm of machine learning, which was widely used in many fields abroad.
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.
针对支持向量机学习是一种有导师的学习，引入了否定算法，把人脸特征否定的结果来供支持向量机学习。
Because the learning support vector machine is an instructing learning, a negative algorithm is introduced. The negative result of facial feature is provided for the support vector machine learning.
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。
Support vector machine is a new machine learning algorithm, based theoretically on statistic learning theory created by Vapnik.
文中采用的分类器——支持向量机是一种能在训练样本数很少的情况下达到很好分类推广能力的学习算法。
Adopts a classifier support vector machine which is a very good training algorithm, which can acquire very good generalization when the training datum are very few.
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。
Support vector machine is a new learning machine, and it is based on the statistics learning theory.
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。
Support vector machine is a new learning machine, and it is based on the statistics learning theory.
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