FCM,模糊C均值聚类的MATLAB实现[matlab]-FCM
所属分类：数学计算
开发工具：matlab
文件大小：6KB
下载次数：2
上传日期：2018-04-26 14:54:49
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五道杠骚年
说明： 模糊c-均值聚类算法 fuzzy c-means algorithm (FCMA)或称（ FCM）。在众多模糊聚类算法中，模糊C-均值（ FCM） 算法应用最广泛且较成功，它通过优化目标函数得到每个样本点对所有类中心的隶属度，从而决定样本点的类属以达到自动对样本数据进行分类的目的。
(Fuzzy c-means algorithm (FCMA) or FCM. Among many fuzzy clustering algorithms, the fuzzy C-means (FCM) algorithm is the most widely used and successful. It obtains the degree of membership of each sample point to all class centers by optimizing the objective function, thus determining the generic class of sample points to achieve The purpose of classifying sample data automatically.)
文件列表:
FCM,模糊C均值聚类的MATLAB实现[matlab]\calcDataDist.m (495, 2003-01-08)
FCM,模糊C均值聚类的MATLAB实现[matlab]\calcMub.m (789, 2003-01-08)
FCM,模糊C均值聚类的MATLAB实现[matlab]\calcStatYm.m (614, 2002-10-23)
FCM,模糊C均值聚类的MATLAB实现[matlab]\fcm.m (1466, 2002-01-31)
FCM,模糊C均值聚类的MATLAB实现[matlab]\fcm_calcC.m (601, 2002-01-31)
FCM,模糊C均值聚类的MATLAB实现[matlab]\fcm_calcD.m (625, 2002-01-31)
FCM,模糊C均值聚类的MATLAB实现[matlab]\fcm_calcU.m (896, 2002-01-31)
FCM,模糊C均值聚类的MATLAB实现[matlab]\fcm_dataInitC.m (446, 2002-01-31)
FCM,模糊C均值聚类的MATLAB实现[matlab]\fcm_evalJ.m (455, 2002-01-31)
FCM,模糊C均值聚类的MATLAB实现[matlab]\searchMub.m (1108, 2003-01-08)
FCM,模糊C均值聚类的MATLAB实现[matlab] (0, 2006-05-25)
This file describe the content of fcm.ZIP
Notations used
X = dataset of size (M,N)
M = number of experiments
N = numbre of genes
K = number of clusters
mub = upper bound value of the fuzzy parameter
file description
calcDataDist.m compute the vector of size [N(N-1)/2,1] containing distances
between all pair of genes using the dataset
(computionally expensive for large N)
calcMub.m compute the upper bound value of fuzzy parameter from the
dataset
calcStatYm.m compute mean, std, cv from the [N(N-1)/2] distances vector
fcm.m compute the centroids and the fuzzy partition matrix
fcm_calcC.m used by fcm.m
fcm_calcD.m used by fcm.m
fcm_calcU.m used by fcm.m
fcm_dataInitC.m used by fcm.m
fcm_evalJ.m used by fcm.m
searchMub.m compute the upper bound value of the fuzzy parameter from
the [N(N-1)/2,1] vector of distances
NB : every function has its own help which can be obtained by typing "help name"
where "name" is the function, e.g. "help fcm"
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