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Consider the following frequency counts of some itemsets in a transaction database r:
freq({A}, r) = 0.405
freq({B}, r) = 0.510
freq({C}, r) = 0.303
freq({A,B}, r) = 0.380
freq({A,C}, r) = 0.256
freq({B,C}, r) = 0.197
freq({A,B,C}, r) = 0.095
Based on this information, you can use them to compute the following probabilities. (e.g. P(X) = freq(X, r).)
a) What is the joint probability P(A and B)? What is P(A) ? P(B)?
b) What are the confidence and lift ratio of the association rules generated from the following itemsets: {A, B, C} and { ¯A, B}?
c) Compare the results of a) and b) with the frequencies freq({A}, r) and freq({B}, r). What observations can you made about the relationship of A and B in terms of independence and possible causal relationship? Please explain your answer.
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How the time stamps are implemented Use the value of the system clock as the time stamp. That is a transaction's time stamp is equivalent to the value of the clock when the tra
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