Assosication rule and clustering
- 최초 등록일
- 2009.08.31
- 최종 저작일
- 2009.08
- 12페이지/
MS 워드
- 가격 1,000원
소개글
Datamining에서
SAS를 통한 Assosication rule and clustering
수행 과제
목차
1. Association Rule
2. Clustering
본문내용
1.4 Discussion :
The result of MBA shows association rules having confidence more than 40% . I sorted descending for confidence. This shows rules that related to buy with something. Confidence for A->B means percentage of customers who purchased both A and B, divided by the number of customers who purchased A. Below Confidence column, 100% confidence means all customer who purchased “Brushes” also purchased “NailPolish”. Support for A->B is the percentage of all customers who purchased both A and B. Support is a measure of how frequently the rule occur in the data base. Therefore, more higher support, better rules. This is because many data sets can prove the rule. Lastly, Lift of A-> B is a measure of strength of th association.
At first row, customers having “Brushes” is about three times the number of customers who having “NailPolish” as a customer chosen at random.
This data has only two column. Therefore, It is very difficult to Know meaning of “Association rules”.
참고 자료
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