=== Associator model ===

Scheme:   Apriori
Relation: final-weka.filters.unsupervised.instance.SubsetByExpression-Enot ismissing(ATT13)-weka.filters.unsupervised.instance.SubsetByExpression-EATT10 is '0.0' or ATT10 is '1.0'-weka.filters.unsupervised.instance.SubsetByExpression-Enot (ATT11 is 'Q')-weka.filters.unsupervised.instance.SubsetByExpression-Enot (ATT1=0.1)-weka.filters.unsupervised.attribute.NumericToNominal-Rfirst-last-weka.filters.unsupervised.attribute.MergeTwoValues-Cfirst-F5-S6-weka.filters.unsupervised.attribute.MergeTwoValues-Cfirst-F5-S6-weka.filters.unsupervised.attribute.MergeTwoValues-Cfirst-F5-S6-weka.filters.unsupervised.attribute.MergeTwoValues-Cfirst-F5-S6-weka.filters.unsupervised.attribute.Remove-V-R1-4


Apriori
=======

Minimum support: 0.7 (601 instances)
Minimum metric <confidence>: 0.9
Number of cycles performed: 6

Generated sets of large itemsets:

Size of set of large itemsets L(1): 4

Size of set of large itemsets L(2): 6

Size of set of large itemsets L(3): 4

Size of set of large itemsets L(4): 1

Best rules found:

 1. Punishment=30 816 ==> Survey=20 816    conf:(1)
 2. Survey=20 816 ==> Punishment=30 816    conf:(1)
 3. Prize=10 Punishment=30 773 ==> Survey=20 773    conf:(1)
 4. Survey=20 Prize=10 773 ==> Punishment=30 773    conf:(1)
 5. Rating=0.9_0.925_0.94_0.95_1 687 ==> Survey=20 687    conf:(1)
 6. Rating=0.9_0.925_0.94_0.95_1 687 ==> Prize=10 687    conf:(1)
 7. Rating=0.9_0.925_0.94_0.95_1 687 ==> Punishment=30 687    conf:(1)
 8. Rating=0.9_0.925_0.94_0.95_1 Prize=10 687 ==> Survey=20 687    conf:(1)
 9. Rating=0.9_0.925_0.94_0.95_1 Survey=20 687 ==> Prize=10 687    conf:(1)
10. Rating=0.9_0.925_0.94_0.95_1 687 ==> Survey=20 Prize=10 687    conf:(1)
11. Rating=0.9_0.925_0.94_0.95_1 Punishment=30 687 ==> Survey=20 687    conf:(1)
12. Rating=0.9_0.925_0.94_0.95_1 Survey=20 687 ==> Punishment=30 687    conf:(1)
13. Rating=0.9_0.925_0.94_0.95_1 687 ==> Survey=20 Punishment=30 687    conf:(1)
14. Rating=0.9_0.925_0.94_0.95_1 Punishment=30 687 ==> Prize=10 687    conf:(1)
15. Rating=0.9_0.925_0.94_0.95_1 Prize=10 687 ==> Punishment=30 687    conf:(1)
16. Rating=0.9_0.925_0.94_0.95_1 687 ==> Prize=10 Punishment=30 687    conf:(1)
17. Rating=0.9_0.925_0.94_0.95_1 Prize=10 Punishment=30 687 ==> Survey=20 687    conf:(1)
18. Rating=0.9_0.925_0.94_0.95_1 Survey=20 Punishment=30 687 ==> Prize=10 687    conf:(1)
19. Rating=0.9_0.925_0.94_0.95_1 Survey=20 Prize=10 687 ==> Punishment=30 687    conf:(1)
20. Rating=0.9_0.925_0.94_0.95_1 Punishment=30 687 ==> Survey=20 Prize=10 687    conf:(1)
21. Rating=0.9_0.925_0.94_0.95_1 Prize=10 687 ==> Survey=20 Punishment=30 687    conf:(1)
22. Rating=0.9_0.925_0.94_0.95_1 Survey=20 687 ==> Prize=10 Punishment=30 687    conf:(1)
23. Rating=0.9_0.925_0.94_0.95_1 687 ==> Survey=20 Prize=10 Punishment=30 687    conf:(1)
24. Prize=10 816 ==> Survey=20 773    conf:(0.95)
25. Survey=20 816 ==> Prize=10 773    conf:(0.95)
26. Punishment=30 816 ==> Prize=10 773    conf:(0.95)
27. Prize=10 816 ==> Punishment=30 773    conf:(0.95)
28. Survey=20 Punishment=30 816 ==> Prize=10 773    conf:(0.95)
29. Punishment=30 816 ==> Survey=20 Prize=10 773    conf:(0.95)
30. Prize=10 816 ==> Survey=20 Punishment=30 773    conf:(0.95)
31. Survey=20 816 ==> Prize=10 Punishment=30 773    conf:(0.95)