x := Array(22,35,24,32,43,53);
y := Array(1,2,3,4,5,6);
name := 'euclidean'; //采用欧式距;
return Distance(x,y,name);
结果 80.04998438475;
x :=array(
(700.9,39.77,8.49,12.94,19.27,11.05,2.04,13.29),
(7.68,50.37,11.35,13.3,19.25,14.59,2.75,14.87),
(9.42,27.93,8.2,8.14,16.17,9.42,1.55,9.76),
(9.16,27000.98,9.01,9.32,15.99,9.1,1.82,11.35),
(10.06,28.64,10.52,10.05,16.18,8.39,1.96,10.81)) ;
name := "euclidean";
return Distance(x,name);
结果
array(
(0,693.32,691.62,26970.08,690.96),
(693.32,0,24.64,26950.61,23.54),
(691.62,24.64,0,26973.05,3.5),
(26970.08,26950.61,26973.05,0,26972.34),
(690.96,23.54,3.5,26972.34,0));
Corr Covariance Cluster_Kmeans Cluster_System Cluster_ward