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1、DataMiningYingLiu,Prof.,Ph.DUniversityofChineseAcademyofSciencesReview?Datamining—coreofPatternEvaluationknowledgediscoveryprocessDataMiningSelectionandTransformationDataWarehouseDataCleaningandIntegrationDatabasesFlatfiles2017/10/212MiningAssociationRule
2、sinLargeDatabases?Basicconceptsandaroadmap?Miningsingle-dimensionalBooleanassociationrules?Miningmultilevelassociationrules?Miningmultidimensionalassociationrules?Summary2017/10/213MarketBasketAnalysis2017/10/214WhatIsAssociationRulesMining??Associationru
3、lesmining?Findingfrequentpatterns,associationsamongsetsofitemsorobjectsintransactiondatabases,relationaldatabases,andotherinformationrepositories.?Examples?Whatproductswereoftenpurchasedtogether?—Beeranddiapers?!?WhatDNAsegmentsoftenoccurtogetherinDNAsequ
4、ences?2017/10/215WhatIsAssociationRulesMining??Wheredoesthedatacomefrom??supermarkettransactions,membershipcards,discountcoupons,customercomplaintcalls?Applications?Basketdataanalysis?Cross-marketing?Catalogdesign?Salecampaignanalysis?Weblog(clickstream)a
5、nalysis?DNAsequenceanalysis2017/10/216BasicConceptsTransaction-idItemsbought10A,B,D20A,C,D30A,D,E40B,E,F50B,C,D,E,F?ItemcollectionX={x,…,x}1m?Itemset:asetofitems,k-itemset?TransactionT?X,eachTassociatesauniqueTidanditemsboughtbyacustomer?Ruleform?=>?,??X,
6、??X,???=?2017/10/217BasicConcepts?support,s,probabilitythataCustomertransactioncontains?and?Customerbuysbothbuys??support(?=>?)=P(???)?Frequentitemset,occurrencegreaterthanamin_support?Frequentitemsetmining,findalltherules?=>?satisfyingCustomerbuys?min_su
7、pport?Letsup=50%,minfrequentItemsets{A:3,B:3,D:4,E:3,AD:3}support(A)=3/5=60%,support(AD)=3/5=60%2017/10/218BasicConcepts?confidence,c,conditionalprobabilitythatatransactionhaving?alsocontains?P(???)count(???)Confidence(?=>?)=P(???)=————=———————P(?)count(?
8、)?Measureofruleinterestingness?Rulessatisfymin_supportandmin_confidencearestrong?Letsup=50%,conf=50%,minminfrequentitemsets{A:3,B:3,D:4,E:3,AD:3}Associationrules:A=>D(60%,100%)D=>A(60%,75%)2017/10/219Interestingness
