Untitled

=== Run information ===

Scheme:       weka.clusterers.SimpleKMeans -init 0 -max-candidates 100 -periodic-pruning 10000 -min-density 2.0 -t1 -1.25 -t2 -1.0 -N 2 -A "weka.core.EuclideanDistance -R first-last" -I 500 -num-slots 1 -S 10
Relation:     MarriedData
Instances:    10
Attributes:   4
              Refund
              Marital Status
              Taxable Income
              Cheat
Test mode:    evaluate on training data


=== Clustering model (full training set) ===


kMeans
======

Number of iterations: 3
Within cluster sum of squared errors: 9.296595982142858

Initial starting points (random):

Cluster 0: yes,married,120,no
Cluster 1: yes,divorced,220,no

Missing values globally replaced with mean/mode

Final cluster centroids:
                              Cluster#
Attribute         Full Data          0          1
                     (10.0)      (7.0)      (3.0)
=================================================
Refund                   no         no        yes
Marital Status       single     single     single
Taxable Income          104    82.1429        155
Cheat                    no         no         no




Time taken to build model (full training data) : 0 seconds

=== Model and evaluation on training set ===

Clustered Instances

0       7 ( 70%)
1       3 ( 30%)