K-means算法属于弱监督聚类算法吗
怎样用matlab实现多维K-means聚类算法 function[labels]=kmeans_clustering(data，k)[num，~]=size(data)；ind=randperm(num)；ind=ind(1：k)；centers=data(ind，：)；d=inf；labels=nan(num，1)；while d>；0labels0=labels；dist=pdist2(data，centers)；[~，labels]=min(dist，[]，2)；d=sum(labels0~=labels)；for i=1：kcenters(i，：)=mean(data(labels=i，：)，1)；endendend
请问 谁有MATLAB K-MEANS聚。 请问谁有MATLABK-MEANS聚类算法工具包？B.20世纪上半叶，人类经历了两次世界大战，大量的青壮年人口死于战争；而20世纪下半叶，世界基本处于和平发展时期。。
matlab对一维数据进行K-means聚类离散化并显示，目前，数据挖掘技术十分热门，数据挖掘中有一种关联规则挖掘方法，在关联规则挖掘前需要将采集的连续数据离散化才行。。
怎样用matlab实现多维K-means聚类算法 直接用kmeans函数。idx=kmeans(X，k)idx=kmeans(X，k，Name，Value)[idx，C]=kmeans(_)[idx，C，sumd]=kmeans(_)[idx，C，sumd，D]=kmeans(_)idx=kmeans(X，k)performs k-means clustering to partition the observations of the n-by-p data matrix X into k clusters，and returns an n-by-1 vector(idx)containing cluster indices of each observation.Rows of X correspond to points and columns correspond to variables.By default，kmeans uses the squared Euclidean distance measure and the k-means+algorithm for cluster center initialization.exampleidx=kmeans(X，k，Name，Value)returns the cluster indices with additional options specified by one or Name，Value pair arguments.For example，specify the cosine distance，the number of times to repeat the clustering using new initial values，or to use parallel computing.example[idx，C]=kmeans(_)returns the k cluster centroid locations in the k-by-p matrix C.example[idx，C，sumd]=kmeans(_)returns the within-cluster sums of point-to-centroid distances in the k-by-1 。
