GIVEN BELOW DATASET, KINDLY PRODUCE THE :

- 1 FREQUENT ITEMSET - 2 FREQUENT ITEMSET - 3 FREQUENT ITEMSET - THE RELEVANT ASSOCIATIVE RULES CREATED SUCH THAT THE SAME OUTPUT IS OBTAINED AS WEKA

KINDLY PROVIDE CLEAR EXPLANAITIONS WITH ALL CALCULATIONS

THE DATASET : young,myope,no,reduced,none young,myope,no,normal,soft young,myope,yes,reduced,none young,myope,yes,normal,hard young,hypermetrope,no,reduced,none young,hypermetrope,no,normal,soft young,hypermetrope,yes,reduced,none young,hypermetrope,yes,normal,hard pre-presbyopic,myope,no,reduced,none pre-presbyopic,myope,no,normal,soft pre-presbyopic,myope,yes,reduced,none pre-presbyopic,myope,yes,normal,hard pre-presbyopic,hypermetrope,no,reduced,none pre-presbyopic,hypermetrope,no,normal,soft pre-presbyopic,hypermetrope,yes,reduced,none pre-presbyopic,hypermetrope,yes,normal,none presbyopic,myope,no,reduced,none presbyopic,myope,no,normal,none presbyopic,myope,yes,reduced,none presbyopic,myope,yes,normal,hard presbyopic,hypermetrope,no,reduced,none presbyopic,hypermetrope,no,normal,soft presbyopic,hypermetrope,yes,reduced,none presbyopic,hypermetrope,yes,normal,none

Apriori Minimum support: 0.2 (5 instances) Minimum metric : 0.9 Number of cycles performed: 16 Generated sets of large itemsets: Size of set of large itemsets L (1): 11 Size of set of large itemsets L(2): 21 Size of set of large itemsets L(3): 6 Best rules found: 1. tear-prod-rate=reduced 12 ==> contact-lenses=none 12 lift:(1.6) lev:(0.19) [4] conv:(4.5) 2. spectacle-prescrip=myope tear-prod-rate=reduced 6 ==> contact-lenses=none 6 lift: (1.6) lev: (0.09) [2] conv: (2.25) 3. spectacle-prescrip=hypermetrope tear-prod-rate=reduced 6 ==> contact-lenses=none 6 lift:(1.6) lev: (0.09) [2] conv: (2.25) 4. astigmatism=no tear-prod-rate=reduced 6 ==> contact lenses=none 6 lift:(1.6) lev: (0.09) [2] conv: (2.25) 5. astigmatism=yes tear-prod-rate=reduced 6 ==> contact-lenses=none 6 lift:(1.6) lev: (0.09) [2] conv: (2.25) 6. contact-lenses=soft 5 ==> astigmatism=no 5 lift: (2) lev:(0.1) [2] conv: (2.5) 7. contact-lenses=soft 5 ==> tear-prod-rate=normal 5 lift:(2) lev:(0.1) [2] conv: (2.5) 8. tear-prod-rate=normal contact-lenses=soft 5 ==> astigmatism=no 5 lift:(2) lev:(0.1) [2] conv: (2.5) 9. astigmatism=no contact-lenses=soft 5 ==> tear-prod-rate=normal 5 lift: (2) lev: (0.1) [2] conv: (2.5) 10. contact-lenses=soft 5 ==> astigmatism=no tear-prod-rate=normal 5 lift: (4) lev: (0.16) [3] conv: (3.75) weka.gui.GenericObjectEditor weka.associations.Apriori About Class implementing an Apriori-type algorithm. More Capabilities car False classIndex -1 delta 0.05 doNotCheckCapabilities False lowerBound MinSupport 0.1 metricType Confidence minMetric 0.9 numRules 10 outputItemSets False