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https://en.wikipedia.org/wiki/Association_rule_learning
Association rule learning is a rule-based machine learning method for discovering interesting relations between variables in large databases. It is intended to identify strong rules discovered in databases using some measures of interestingness. Based on the concept of strong rules, Rakesh Agrawal, Tomasz Imieliński and Arun Swami introduced association rules for discovering regularities ...
https://stackoverflow.com/questions/18589186/how-to-calculate-support-confidence-and-lift-for-merged-itemsets-like-a-b-c
For an association rule X--> Y, the support of the rule is denoted as sup(X-> Y) and is the number of transactions where XUY appears divided by the total number of transactions. the confidence is the number of transactions where XUY appears divided by the number of transactions where X appears.
https://www.researchgate.net/publication/233754781_Support_vs_Confidence_in_Association_Rule_Algorithms
Support vs Confidence in Association Rule ... rule mining algorithm is the naive method of finding the frequent item-setsin a huge database by generate a setof all possible combination of items ...
https://www.youtube.com/watch?v=iuIEVNhWtlw
Jul 22, 2014 · Apriori Algorithm Video, ... Support and Confidence - Duration: 8:44. Last Minute Tutorials 52,685 views. 8:44. Data Mining Association Rule - Basic Concepts - Duration: 6:53. IT MinerAuthor: Chris Kimmer
https://csucidatamining.weebly.com/assign-7.html
For each of the following questions, provide an example of an association rule from the market basket domain that satisfies the following conditions. Also, describe whether such rules are subjectively interesting. (a) A rule that has high support and high confidence. Support is how often a rule is applicable for the provided data set.
https://www.it.uu.se/edu/course/homepage/infoutv/ht06/dut-ch6-association-2.pdf
Rule generation algorithm •Key fact: •Algorithm –For each itemset I with minsup: •Find all minconf rules with a single consequent of the form (I - L 1 㱺 L 1) •Repeat: –Guess candidate consequents C k by appending items from I - L k-1 to L k-1 –Verify confidence of each rule I - C k 㱺 …
http://facweb.cs.depaul.edu/mobasher/classes/ect584/Lectures/Liu-Ch2-4.pdf
strength of a rule is measured by its support and confidence. Support: The support of a rule, X → Y, is the percentage of transactions in T that contains X ∪ Y, and can be seen as an estimate of the probability, Pr(X∪Y). The rule support thus determines how frequent the rule is ap-plicable in the transaction set T.
https://www-users.cs.umn.edu/~kumar/dmbook/ch6.pdf
Association Analysis: Basic Concepts and Algorithms ... low support rule is also likely to be uninteresting from a business perspective ... requires us to compute the support and confidence for 36 −27 +1 = 602 rules. More than 80% of the rules are discarded after applying minsup = 20% and
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