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Steve Gunn 开发的svm工具箱源代码，用于分类和回归-Developed by Steve Gunn，used in classification and
regression
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SVM实现数据分类，可自行选取核函数，用于图像分割操作。程序可自动训练分类平面。-SVM for data classification, are free to select the kernel function，For image segmentation operation. The program can automatically train classifiers plane.
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实现基于OpenCV的SVM目标分类,SVM提取目标跟背景-object classification based on SVM
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一篇svm多类分类的综述文章，介绍了现有的经典多类分类方法-a article about multiclass svm，introduced the existing classical methods for multiclass classification
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用matlab编写的用于线性二分类的SVM支撑向量机实例-the demo of svm two classification written in matlab
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简而言之它是个起源跟类神经网络有点像的东西， 不过现今最常拿来就是做分类。 也就是说，如果我有一堆已经分好类的东西。那当收到新的东西时， SVM 可以预测新的资料要分到哪一堆去。-In short, it is a origin with neural network is a bit like things, but now it is most often do classification. That is, if I have a heap of the things which ha
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利用SVM进行分类的简单例子 matlab-an esample of classification using SVM
matlab
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A support vector machine (SVM) is a concept in statistics and computer science for a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis.
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Image Classification Using SVMs
describe SVM
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联合运用粗糙集(RS)理论-遗传算法(GA)-支持向量机(SVM)方法研究真核生物翻译起始位点(TIS)的识别.-A classification model is built to recognize translation initiation sites (TISs) in eukaryotes by applying rough sets-genetic algorithm-support vector machine (RS-GA-SVM).
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SVM源代码，带注解，详细，有使用说明，分类清晰-SVM classification
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支持向量机，SVM算法源代码，干净简洁，使用方便-svm classification
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多种分类模式的文本分类器，支持SVM，KNN,贝叶斯等-svm，knn classification
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关于metric learning的综述，涉及到许多的知识：SVM、kernel、SDP等-This paper surveys the field of distance
metric learning from a principle perspective, and includes a broad selection of recent work. In particular, distance metric learning is reviewed under different
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使用交叉验证的svm matlab 代码，简单，比较好用-svm classification
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SVM分类，算法，代码
-SVM classification algorithm, the code
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利用svm算法分类图像。示例中：将篮球场和网球场利用算法自动分类，包含了基于颜色矩的彩色图像特征提取算法-image classification using SVM algorithm
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有良好的分类能力，接口函数易用，是一个完整c环境下开发的libsvm，比svm分类效果好。- Have good ability of classification，Interface function is easy to use。Is a complete c environment of development libsvm, SVM classification than effect is good.
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对“data3.m”数据，用其中一半的数据采用非线性SVM算法设计分类器并画出决策面，另一半数据用于测试分类器性能。采用三套核函数，并且比较不同核函数的结果。-To "data3.m" data, which half of the data using nonlinear SVM classification algorithm design and draw the decision-making surface, the other half of the data used to tes
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SVM中文分词分类器的python实现，在LINUX环境下运行不需太多配置和代码修改。-SVM for Chinese word classification python implementation running under LINUX environment without too much configuration and code changes.
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