clustervisualtest.m

聚类分析工具箱 亚历山大博士写的

% CLUSION on IRIS data with pre-computed Euclidean similarities

function ClusterVisualTest

% The similarity matrix (e.g., from data matrix x using using simeucl(x))
s = [1 4.57689635160809e-12 3.40706402242985e-10 0.0115623632874686 0.364218979571527 0.932393819905955 8.87524407992262e-09 5.53272656609792e-08 0.740818220681709 2.63974083545828e-08;4.57689635160809e-12 1 0.763379494336845 2.46680912923671e-05 8.42346375446853e-12 2.6406394821914e-12 0.229925485186724 0.132655465080124 7.67859066327913e-11 0.313486180882606;3.40706402242985e-10 0.763379494336845 1 0.000269215064905658 6.39713945274538e-10 2.12942274220307e-10 0.496585303791401 0.269820056384686 4.49634946228087e-09 0.501576069066042;0.0115623632874686 2.46680912923671e-05 0.000269215064905658 1 0.00200923746407007 0.00831245738192307 0.000675538775193837 0.0124007292204434 0.0141223024101641 0.0070834089290521;0.364218979571527 8.42346375446853e-12 6.39713945274538e-10 0.00200923746407007 1 0.467666427009914 5.21052565397045e-08 3.00621178804092e-08 0.677056874498174 1.43430547707768e-08;0.932393819905955 2.6406394821914e-12 2.12942274220307e-10 0.00831245738192307 0.467666427009914 1 8.11136234153499e-09 4.13993771878517e-08 0.718923733431927 1.49284059402559e-08;8.87524407992262e-09 0.229925485186724 0.496585303791401 0.000675538775193837 5.21052565397045e-08 8.11136234153499e-09 1 0.19592957412691 1.3745077279214e-07 0.208045182357022;5.53272656609792e-08 0.132655465080124 0.269820056384686 0.0124007292204434 3.00621178804092e-08 4.13993771878517e-08 0.19592957412691 1 2.47959601804501e-07 0.631283645506939;0.740818220681709 7.67859066327913e-11 4.49634946228087e-09 0.0141223024101641 0.677056874498174 0.718923733431927 1.3745077279214e-07 2.47959601804501e-07 1 1.62921067808257e-07;2.63974083545828e-08 0.313486180882606 0.501576069066042 0.0070834089290521 1.43430547707768e-08 1.49284059402559e-08 0.208045182357022 0.631283645506939 1.62921067808257e-07 1];

% The labeling
cn = [1 3 3 2 1 1 3 3 1 3];

% Do the visualization
clusion(s,cn);