> Java weka.clusterers.simplekmeans-p 1-l G:\Program\data_Factory\example.model-T G:\Program\data_Factory\ Save_file_id2class.arff 0 1 (0)1 2 (0)2 1 (0)3 3 ($)4 1 (0)> Java weka.clusterers.simplekmeans-l G:\Program\data_Factory\example.model-T G:\Program\data_Factory\save_ File_id2class.arffKmeans======Number of Iterations:8within cluster sum of squared errors:252.54315798169944Missing values globally replaced with Mean/modeCluster centroids:cluster#Attribute Full Data 0 1 2 3(+) (9) (139 ) (+)==================================================================H00 7.66 57.5556 2.9281 3.3793 22.1304H01 3.265 45.5556 0.1799 0 9.4783H02 2.015 28.4444 0.1007 0 5.7826H03 1.96 19.6667 0.2734 0 7.6957H04 1.505 17.6667 0.3957 0.4828 3.1739H05 1.13 13.1111 0 0.8621 3.6087H06 1.855 8 1.1583 2.0345 3.4348H07 2.49 6.5556 1.0719 5.1724 6.087H08 3.51 7.5556 0.5899 14.1724 6.1304H09 5.295 18.5556 0.223 21.8966 9.8261H10 7.12 23.6667 0.8921 14.4783H11 8.195 25.2222 0.7194 24.7931 25.7826H12 10.505 20.7778 1.554 29.7241 36.3478H13 11.245 7.2222 2.3381 30.7241 42.087H14 10.32 0.3333 4.5396 11.1724 48.087H15 10.55 0 4.8993 7.2069 53.0435H16 9.71 0 4.8921 4.5517 49.1304H17 10.72 5.6667 5.7914 8.0345 45.8696H18 12.315 0 7.2518 15.6552 43.5217H19 14.185 0 10.0647 16.2759H20 16.68 0 12.8417 25.2414 35.6087H21 18.07 4.3333 15.4748 22.7241 33.2609H22 16.875 15.6667 13.1511 19.4483 36.6087H23 7.375 14.6667 4.4173 7.5172 22.2174= = = Clustering stats for training data = = == = = Clustering Stats for testing data = = =Clustered Instances1 3 (60%)2 1 (20%)3 1 (20%)
From for notes (Wiz)
Weka Cluster prediction
