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https://www.quora.com/What-is-support-and-confidence-in-data-mining
So, there has to be a way to evaluate the importance of a discovered rule. Here comes the support and confidence. Suppose the rule we discovered is as follows: [math]Wine → Cheese [Support: 9\%, Confidence: 65\%][/math] Support: is the percentage of transactions in T that contain both wine and Cheese together. (9% of all baskets had these 2 items together.)
https://searchcustomerexperience.techtarget.com/answer/Confidence-and-support-in-data-mining
Sep 21, 2001 · Support used in Data Mining/Intelligence These are fairly ubiquitous words in and out of the spaces of DM/BI/mining, but confidence can refer to the anticipated range of an output variable given a set of input variable values.
https://www.answers.com/Q/What_is_the_difference_between_support_and_confidence_data_mining
Apr 23, 2014 · What is the difference between support and confidence data mining? Answer. Wiki User April 23, 2014 6:45AM. supoort meand the uninon of probhabilty of A union B.
https://t4tutorials.com/support-confidence-minimum-support-frequent-itemset-in-data-mining/
Support, Confidence, Minimum support, Frequent itemset, K-itemset, absolute support in data mining – Click Here; Apriori Algorithm in Data Mining with examples – Click Here; Apriori principles in data mining, Downward closure property, Apriori pruning principle – Click Here; Apriori candidates’ generations, self-joining, and pruning principles.
https://www.researchgate.net/publication/233754781_Support_vs_Confidence_in_Association_Rule_Algorithms
Hence, a data mining language needs to be provided such that users can query only interesting knowledge to them from a large database of customer transactions. A …
https://stats.stackexchange.com/questions/229523/association-rules-support-confidence-and-lift
I know that support is P(XY), confidence is P(XY)/P(X) and lift is P(XY)/P(X)P(Y), where the lift is a measurement of independence of X and Y (1 represents independent) However, I just don't know how to interpret rules with these indicators. I have rules with high support,...
https://docs.oracle.com/cd/B28359_01/datamine.111/b28129/algo_apriori.htm
Support and confidence are also the primary metrics for evaluating the quality of the rules generated by the model. Additionally, Oracle Data Mining supports lift for association rules. These statistical measures can be used to rank the rules and hence the usefulness of the predictions.
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