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Support Vector Machines is a powerful methodology for solving problems in nonlinear classification and regression.
It is a matlab version.-Support Vector Machines is a powerful methamphetamine odology for solving problems in nonlinear CLAS sificati
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SVM的matlab接口．为利用SVM进行分类提供了一个matlab的环境-SVM Matlab interface. For the use of SVM classification of a Matlab environment
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SVM的VC程序，有matlab接口，便于调用，还有例子，用于模式识别，分类，预测。-SVM, VC procedures, matlab interface, easy call, as well as an example, for pattern recognition, classification and prediction
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支撑向量机SVM的工具LIBSVM，能够在windows平台下通过命令行使用，也可以在matlab下调用，适合于研究复杂条件下的分类问题-Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM
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svm多分类器，包括多分类和GA算法和PSO算法优化的SVM-svm multi-classifier, including the multi-classification and GA algorithm and PSO algorithm for optimization of SVM
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This program implements SVM classification over libsvm library.
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是一種線性方成的分類器。SVM透過統計的方式將雜亂的資料以NN的方式分成兩類，以便處理。LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM. -Main features of LIBLINEA
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SVM是一种比较新比较流行的算法，常常用在分类问题和回归问题上。
libsvm相关的matlab代码-SVM is a relatively new algorithm is more popular, often used in classification and regression issues. libsvm-related matlab code
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SVM是一种优秀的分类算法，常用于用于回归分析和分类，而matlab语言的libSVM则为广大使用matlab进行设计的人员提供很好的帮助。-libSVM for regression classification
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libsvm工具箱，用于分类的绝佳工具，也可用于非线性回归及预测，或拟合，其中文本分类是其长项，回归性能非常好-libsvm toolbox, an excellent tool for the classification can also be used for non-linear regression and forecasting, or fitting, of which text categorization is its long entry and return to a ve
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台湾大学林智仁开发的libsvm的matlab最新版，可以实现分类、回归、预测的功能-Lin Zhiren Taiwan University developed the matlab libsvm latest version can be achieved classification, regression, prediction of functional
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SVM matlab 工具箱，可以进行SVM分类-SVM matlab toolbox, SVM classification can be
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This folder contains a matlab program for machine learning (classification using SVMs)
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根据训练数据，使用SVMlib 学习TrainLetter.txt的linear SVM models, 进而预测测试数据TestLetter.txt的分类结果(According to the training data, the TrainLetter.txt linear SVM models is learned by using SVMlib, and then the classification results of the test data TestLetter.txt are
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支持向量机，用于模式识别的特征分类，基于MATLAB的工具包(Support vector machines are used for feature classification of pattern recognition, based on MATLAB Toolkit)
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LIBSVM工具箱，提供支持向量机分类及回归预测(LIBSVM Toolbox provides support vector machine classification recognition and regression prediction)
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svm library using matlab
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支持向量机matlab实例及理论,详细介绍了svm理论以及MATLAB自带的SVM分类用法(Support vector machine matlab examples and theories, detailing svm theory and MATLAB comes with SVM classification)
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Code classification by using svm with language matlab and c++
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SVM(Support Vector Machine)指的是支持向量机，是常见的一种判别方法。在机器学习领域，是一个有监督的学习模型，通常用来进行模式识别、分类以及回归分析。
Vapnik等人在多年研究统计学习理论基础上对线性分类器提出了另一种设计最佳准则。其原理也从线性可分说起，然后扩展到线性不可分的情况。甚至扩展到使用非线性函数中去，这种分类器被称为支持向量机(Support Vector Machine，简称SVM)。支持向量机的提出有很深的理论背景。
支持向量机方法是在后来提出的
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