algorithm = c("Hartigan-Wong", "Lloyd", "Forgy", "MacQueen"), trace=FALSE) #x为数据集,centers为预设类别数K,iter.max为迭代的最大值,默认为10 #nstart为选择随机起始中心点的次数,默认为1,algorithm算法选择默认为Harttigan-Wong iris2<-iris[,1:3]#调用数据集iris前3列作为原始数据集 fit_km1=...
defkmedoids( data, k):'''given the data and # of clusters, compute the best clustering based on the algorithm provided in wikipedia: google pam algorithm.'''#cur_medoids compare with old_medoids, convergence achieved if no change in the list of medoids in consecutive iterations.#tmp_medoids...
AI检测代码解析 importjava.util.ArrayList;importjava.util.Collections;importjava.util.List;importjava.util.Random;publicclassPAMAlgorithm{publicstaticList<Integer>initializeMedoids(intk,intdataSize){List<Integer>medoids=newArrayList<>();Randomrandom=newRandom();for(inti=0;i<k;i++){intmedoid=random.nex...
聚类分析中PAM算法的分析与实现
Efficient PAM algorithm based on grid structure WANG Shi-qing 1,ZHANG Shu-chun 2 (1.School of Software Technology,Zhengzhou University,Zhengzhou 450002,China;2.School of Information Engineering,Zhengzhou University,Zhengzhou 450002,China )Abstract ：To improve the efficiency of standard PAM algorithm ...
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数据场聚类PAM is a k-mediod algorithm. It is efficient and flexible to handle data sets. However, there are inaccurate and insufficient in random choosing initial data center in algorithm PAM, and PAM is not robust to treat data sets in- cluding outlier or noise. Based on data field ...
Then an instance of implementation of PAM algorithm is demonstrated.Keywords:PAM algorithm;medoid;dissimilarity;cost0 引 言聚类就是将一组数据对象划分成多个类或簇 , 在同一个簇中的对象之间具有较高的相似度 , 而在不同簇中的对象差别较大。在最近几十年中 , 聚类分析广泛地应用在许多领域中 , ...
[Keywords]PAM clustering algorithm: center; Clustering analysis; cost 引言 如今数据挖掘地理论越来越广泛地应用在商业、制造业、金融业、医药业、 电信业等等许多领域.数据挖掘地LI标之一是进行聚类分析.聚类就是把一组个体 按照相似性归成若干类别,它地LI地是使得属于同一类别地个体之间地差别尽可 能地小,而不...