The original association rule mining formulation uses the support and confidence measures to prune uninteresting rules. (a)

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The original association rule mining formulation uses the support and confidence measures to prune uninteresting rules.
The original association rule mining formulation uses the support and

(a) Draw a contingency table for each of the following rules using the transactions shown in Table 6.4.
Rules: {b} †’ {c}, {a} †’ {d}, {b} †’ {d}, {e} †’ {c}, {c} †’ {a}.
(b) Use the contingency tables in part (a) to compute and rank the rules in decreasing order according to the following measures.
i. Support.
ii. Confidence.
iii.

The original association rule mining formulation uses the support and

iv.

The original association rule mining formulation uses the support and

v. Klosgen(X †’ Y ) = ˆšP(X, Y ) × (P(Y|X) ˆ’ P(Y)), where P(Y|X) = P(X,Y)/P(X).
vi.

The original association rule mining formulation uses the support and
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Introduction to Data Mining

ISBN: 978-0321321367

1st edition

Authors: Pang Ning Tan, Michael Steinbach, Vipin Kumar

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