classification
所属分类：人工智能/神经网络/深度学习
开发工具：Visual C++
文件大小：98KB
下载次数：847
上传日期：2009-02-16 18:42:30
上 传 者：
tangxiaojun375
说明： 该程序包实现了几个常用的模式识别分类器算法，包括K近邻分类器KNN、线性判别方程LDF分类器、二次判别方程QDF分类器、RDA规则判别分析分类器、MQDF改进二次判别方程分类器、SVM支持向量机分类器。 主程序中还有接口调用举例，压缩包中还有两个测试数据集文件。
(The package to achieve a number of commonly used pattern recognition classifier algorithms, including K neighbor classifier KNN, linear discriminant equation LDF classifier, quadratic discriminant equation QDF classifier, RDA rules of discriminant analysis classifier, MQDF improve the quadratic discriminant equation classifier, SVM Support Vector Machine classifier. Also call the main program interface, for example, compressed package there are two test data sets document.)
文件列表:
classification\global.h (3286, 2008-12-09)
classification\classificationLDF.opt (53760, 2009-02-16)
classification\classificationLDF.dsp (4796, 2008-12-09)
classification\svm.cpp (61138, 2009-02-16)
classification\matrixOperation1.cpp (12847, 2009-02-16)
classification\classificationQDF.cpp (5935, 2009-02-16)
classification\mainProcess.cpp (7138, 2009-02-16)
classification\svm.h (2929, 2008-11-11)
classification\classificationKNN.cpp (6443, 2009-02-16)
classification\classificationSVM.cpp (4162, 2009-02-16)
classification\classificationLDF.dsw (557, 2008-11-04)
classification\classificationMQDF.cpp (8128, 2009-02-16)
classification\classificationLDF.ncb (164864, 2009-02-16)
classification\classificationLDF.cpp (6108, 2009-02-16)
classification\Matrix.cpp (9177, 2009-02-16)
classification\classificationRDA.cpp (12955, 2009-02-16)
classification\trainData.cpp (4305, 2009-02-16)
classification\Matrix.h (1096, 2008-12-09)
classification\classificationLDF.plg (1540, 2009-02-16)
classification\matrixOperation1.h (1107, 2008-11-04)
data\iris-test.data (1119, 2008-11-12)
data\iris-train.data (3429, 2008-11-13)
data\newVowel-test.data (45251, 2009-01-12)
data\newVowel-train.data (51659, 2009-01-12)
classification\Release (0, 2008-11-05)
classification\Debug (0, 2008-11-04)
classification (0, 2008-11-04)
data (0, 2009-02-16)
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