title: How to interpret output of EM on weka
body: <p>I tried to run the EM algorithm on data with the default parameters in WEKA and but I am not able to understand how to interpret it?</p>
  
  <pre>
      === Run information ===
  
  Scheme:       weka.clusterers.EM -I 100 -N -1 -X 10 -max -1 -ll-cv 1.0E-6 -ll-iter 1.0E-6 -M 1.0E-6 -K 10 -num-slots 1 -S 100
  Relation:     Chronic_Kidney_Disease-weka.filters.unsupervised.attribute.Remove-R12-weka.filters.unsupervised.attribute.Remove-R3-weka.filters.unsupervised.attribute.Remove-R3-4-weka.filters.unsupervised.attribute.Remove-R5-10,12-20
  Instances:    800
  Attributes:   6
                age
                bp
                rbc
                pc
                hemo
                class
  Test mode:    evaluate on training data
  
  
  === Clustering model (full training set) ===
  
  
  EM
  ==
  
  Number of clusters selected by cross validation: 6
  Number of iterations performed: 100
  
  
                Cluster
  Attribute           0        1        2        3        4        5
                 (0.29)   (0.22)   (0.38)   (0.02)   (0.04)   (0.05)
  ===================================================================
  age
    mean         53.5869  65.0962    46.44  51.3652  56.1297   10.939
    std. dev.    12.4505   7.9718   15.546   3.7759  10.2604   6.7004
  
  bp
    mean         77.3114     79.7  71.4394  115.138  92.1235  66.5196
    std. dev.    11.7858  12.1008   8.4722  31.4278   5.8351  10.0583
  
  rbc
    normal      185.8341 165.6585 306.8285  14.0588   7.3129  32.3071
    abnormal     45.4643  13.3988   1.0652   3.3197  29.7885   6.9635
    [total]     231.2984 179.0574 307.8937  17.3785  37.1015  39.2706
  pc
    normal       152.713 147.8797 306.8886  13.0467   1.9999  31.4721
    abnormal     78.5854  31.1776    1.005   4.3319  35.1016   7.7985
    [total]     231.2984 179.0574 307.8937  17.3785  37.1015  39.2706
  hemo
    mean         10.6591  11.7665  15.0745   9.5796   8.1499  12.0494
    std. dev.     2.1313   1.1677   1.3496   2.5159   2.1512   1.5108
  
  class
    ckd         230.1835  177.972   7.2109  16.3651  36.1014   38.167
    notckd        1.1149   1.0853 300.6828   1.0134        1   1.1036
    [total]     231.2984 179.0574 307.8937  17.3785  37.1015  39.2706
  
  
  Time taken to build model (full training data) : 13.21 seconds
  
  === Model and evaluation on training set ===
  
  Clustered Instances
  
  0      218 ( 27%)
  1      196 ( 25%)
  2      302 ( 38%)
  3       12 (  2%)
  4       34 (  4%)
  5       38 (  5%)
  
  
  Log likelihood: -11.18988
  </pre>
  
  <p>Please help in understanding the output.</p>
  
  <p>Thanks in advance</p>