association rules in data mining ppt

What are the rules of data mining?
Introduction Data mining is the discovery of knowledge and useful information from the large amounts of data stored in databases. Association Rules: describing association relationships among the attributes in the set of relevant data. Rules Body ==> Consequent [ Support , Confidence ] Body: represents the examined data.
What is association rule mining?
“ Association rules are if-then statements that help to show the probability of relationships between data items within large data sets in various types of databases. Association rule mining has a number of applications and is widely used to help discover sales correlations in transactional data or in medical data sets. 4 5.
How to generate candidate rule in apriori algorithm?
27. Rule Generation for Apriori Algorithm 30 Candidate rule is generated by merging two rules that share the same prefix in the rule consequent join (CD=>AB,BD=>AC) CD=>AB BD=>AC would produce the candidate rule D => ABC Prune rule D=>ABC if its subset AD=>BC does not have high confidence D=>ABC Prof. Pier Luca Lanzi
How are association rules determined in a transaction data set?
Given a transaction data set T, and a minimum support and a minimum confident, the set of association rules existing in T is uniquely determined. Any algorithm should find the same set of rules although their computational efficiencies and memory requirements may be different.

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PDF	Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe 1.3 Goals of Data Mining and Knowledge Discovery. ?. 1.4 Types of Knowledge Discovered. ? 2 Association Rules. ? 2.1 Association Rules Confidence and

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