KMeans_SPD_Matrices

所属分类：matlab例程

开发工具：matlab

文件大小：23KB

下载次数：5

上传日期：2018-06-07 22:24:17

上 传 者：哈123哈123

说明：  k均值聚类，很实用的matlab程序

K均值算法需要输入待聚类的数据和欲聚类的簇数k，主要的聚类过程有3步：

随机生成k个初始点作为质心

将数据集中的数据按照距离质心的远近分到各个簇中

将各个簇中的数据求平均值，作为新的质心，重复上一步，直到所有的簇不再改变

(K mean clustering, a very practical matlab program

The K mean algorithm needs to input the data to be clustered and the number of clusters to be clustered K. The main clustering process has 3 steps:

Random generation of K initial points as the centroid

The data in the dataset is divided into clusters according to the distance from the centroid.

The average value of the data in each cluster is used as a new centroid to repeat the previous step until all the clusters are no longer changed.)

文件列表：[举报垃圾]

KMeans_SPD_Matrices\DEMO_K_means_8comparison.m, 2956 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\._DEMO_K_means_8comparison.m, 82 , 2014-04-24

KMeans_SPD_Matrices\kmeans_IncKarcherMean.m, 3644 , 2014-04-24

KMeans_SPD_Matrices\kmeans_IncKLsMean.m, 4039 , 2014-04-24

KMeans_SPD_Matrices\kmeans_IncLogEucMean.m, 3549 , 2014-04-24

KMeans_SPD_Matrices\kmeans_IncSteinMean.m, 3391 , 2014-04-24

KMeans_SPD_Matrices\kmeans_KarcherMean.m, 2718 , 2014-04-24

KMeans_SPD_Matrices\kmeans_KLsMean.m, 2761 , 2014-04-24

KMeans_SPD_Matrices\kmeans_LogEucMean.m, 2777 , 2014-04-24

KMeans_SPD_Matrices\kmeans_SteinMean.m, 2713 , 2014-04-24

KMeans_SPD_Matrices\utility\AreAllSym.m, 321 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._AreAllSym.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\distKLs.m, 152 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._distKLs.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\distLogDet.m, 77 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._distLogDet.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\distLogEuc.m, 77 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._distLogEuc.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\expmap.m, 479 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._expmap.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\geod_pn.m, 146 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._geod_pn.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\geodist.m, 378 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._geodist.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\KLS_mean.m, 255 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._KLS_mean.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\LogEuc_mean.m, 164 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._LogEuc_mean.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\logmap.m, 473 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._logmap.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\mean_stein_2.m, 212 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._mean_stein_2.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\meanTensor.m, 645 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._meanTensor.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\meanTensor_logDet.m, 342 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._meanTensor_logDet.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\MtrxExp.m, 445 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._MtrxExp.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\MtrxLog.m, 331 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._MtrxLog.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\MtrxSqrt.m, 98 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._MtrxSqrt.m, 82 , 2014-04-24

KMeans_SPD_Matrices\utility\VectorCrossDist.m, 181 , 2014-04-24

__MACOSX\KMeans_SPD_Matrices\utility\._VectorCrossDist.m, 82 , 2014-04-24

license.txt, 1509 , 2014-04-24

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