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The uploaded Support Vector Machine (SVM) Classifier can classify text-type data well. 详细说明:支持向量机分类器(可分类文本,编的非常不错)
Support Vector Machine (SVM) , which based on Statistic Learning Theory, has the adaptive generation ability. 建立在统计学习理论基础之上的支持向量机具有和样本数相适应的最优泛化能力。
Finally, Support Vector Machine (SVM) was used to validate the correctness of algorithm. 最后利用支持向量机(SVM)作为算法验证的分类器。
Support Vector Machine (SVM) is a novel powerful machine learning method based on SLT. 支持向量机是在该理论体系下产生的一种新的、非常有力的机器学习方法。
This paper introduces a dynamical learning method using support vector machine (SVM). 摘要介绍了用支持向量机(SVM)进行动态学习训练的方法。
We study the models of support vector machine (SVM), and analyze theprocedure of SMO algorithm. 研究了支持向量机(SVM)模型的特点和形式,描述了SMO算法的计算过程和程序框架。
In this paper, we present a new GRF recognition method based on support vector machine (SVM) for the first time. 文中首次提出了使用支持向量机进行运动员脚力曲线自动分段的方法。
Support Vector Machine (SVM) for nonlinear regression has shown very good learning performance. 支持向量机(SVM)在非线性回归估计中具有很好的学习性能。
According to the features of color texture image of plant disease, recognition of plant disease using support vector machine (SVM) and chromaticity moments was introduced. 摘要针对植物病害彩色纹理图像的特点，提出将支持向量机和色度矩分析方法相结合应用于植物病害识别中。
A fault diagnosis approach for the rolling bearing based on the K-L transform (KLT) and support vector machine(SVM) was proposed. 摘要提出了应用K-L变换和支持向量机相结合进行滚动轴承故障诊断的方法。
On the basis of studying Support Vector Machine(SVM) theory,a soft-sensor controlling method based on Support Vector Machine wass presented. 在具体研究支持向量机理论的基础上,提出了一种基于支持向量机的软测量控制方法。
A novel predistorter model based on Support Vector Machine（SVM） is proposed to linearlize nonlinear Power Amplifier（PA） with memory. 提出了一种新的针对记忆非线性功率放大器的支持向量机（SVM）预失真器。
Support vector machine(SVM) is a study machine developing from statical learning theory,which has splendid regression feature. 支持向量机是在统计学理论上发展出的一种学习机器,具有优秀的回归特性。
Abstract: Support vector machine （SVM） is a powerful machine learning technique based on statistical learning theory （SLT）. 文章摘要: 支持向量机是建立在统计学理论之上的强有力的机器学习技术。
The Support vector Machine (SVM), developed from SLT, is an efficient algorithm that applies the SLT to resolve practical problems. 在此理论框架下产生的支持向量机（SVM）方法，使抽象的统计学习理论转化为实际的学习方法。
To deal with customer churn problem in Customer Relationship Management(CRM) systems,prediction model based on Support Vector Machine(SVM) was set up. 针对客户关系管理中的客户流失问题,建立了基于支持向量机的预测模型。
To solve the problem, an improved Local LSI (LLSI) method was proposed, using Support Vector Machine (SVM) to produce the local region. 为解决该问题，提出一种改进的局部潜在语义索引(LLSI)方法，使用支持向量机(SVM)来产生局部区域。
For improving the generalization performance of support vector machine(SVM) effectively，two ensemble algorithms are proposed to train SVM. 摘要为了有效提升支持向量机的泛化性能，提出两种集成算法对其进行训练。
In order to simulate the dynamic process of the Missile Power System, the simulation method based on SVM (Support Vector Machine) was introduced. 为了对导弹动力系统动态过程进行仿真，研究了基于支持向全机方法的动态仿真技术。
A method based on wavelet transform in combination with support vector machine (SVM) is proposed for localizing text region. 摘要提出了一种基于小波变换和支持向量机(SVM)在数字图像中定位文本的方法。