Compute the support for itemsets {P}, {Q, S}, and {P, Q, S} by considering each TID...
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![Compute the support for itemsets {P}, {Q, S}, and {P, Q, S} by considering each TID as a market basket. b.](https://dsd5zvtm8ll6.cloudfront.net/si.experts.images/questions/2023/06/6482b734303a2_1686288179655.jpg)
![TID | Items bought 0001 | {P, S, T} 0003 [P, Q, R, T} 0010 | {P, Q, S, T} 0013 I{P, R, S, T} 0022 IQ, R, T}](https://dsd5zvtm8ll6.cloudfront.net/si.experts.images/questions/2023/06/6482b74402e56_1686288195752.jpg)
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Compute the support for itemsets {P}, {Q, S}, and {P, Q, S} by considering each TID as a market basket. b. Use the results in a. to compute the confidence for the association rules (QSP), and (P⇒ QS). Is confidence a symmetric measure? c. Assuming minimum support=0.4, use the Apriori algorithm to generate all the frequent itemsets. d. Generate all the association rules for the frequent 2-itemsets obtained in c. Calculate the confidence for the rules. TID | Items bought 0001 | {P, S, T} 0003 [P, Q, R, T} 0010 | {P, Q, S, T} 0013 I{P, R, S, T} 0022 IQ, R, T} 0028 {Q, S, T} 0029 | {R, S} 0030 {P, Q, R} 0037 [P, S, T} 0051 I {P, Q, T} Compute the support for itemsets {P}, {Q, S}, and {P, Q, S} by considering each TID as a market basket. b. Use the results in a. to compute the confidence for the association rules (QSP), and (P⇒ QS). Is confidence a symmetric measure? c. Assuming minimum support=0.4, use the Apriori algorithm to generate all the frequent itemsets. d. Generate all the association rules for the frequent 2-itemsets obtained in c. Calculate the confidence for the rules. TID | Items bought 0001 | {P, S, T} 0003 [P, Q, R, T} 0010 | {P, Q, S, T} 0013 I{P, R, S, T} 0022 IQ, R, T} 0028 {Q, S, T} 0029 | {R, S} 0030 {P, Q, R} 0037 [P, S, T} 0051 I {P, Q, T}
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Related Book For
Introduction to Data Mining
ISBN: 978-0321321367
1st edition
Authors: Pang Ning Tan, Michael Steinbach, Vipin Kumar
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