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In context of data mining, what does it mean for an association rule measure to be maximal?

I cannot understand the term maximal in this context.

I know of maximal independent sets in algorithms but cannot make out this term.

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  • $\begingroup$ can you be more precise ? where did you read this ? $\endgroup$
    – AJed
    Jan 13 '13 at 5:49
  • $\begingroup$ but usually, a maximal subset $S$ with certain charatestics is a subset such that there is no other subset $S'$ with the same characteristics and $S \subset S$. That is, cannot extended anymore. $\endgroup$
    – AJed
    Jan 13 '13 at 5:52
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    $\begingroup$ I read it in the following paper infolab.stanford.edu/~sergey/dic.html . If you search for "conviction is truly a measure of implication because it is directional, it is maximal for perfect implications". This is the statement I cannot make out $\endgroup$
    – user1008
    Jan 13 '13 at 6:20
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I believe that in the context of that paper (PS), you can read "maximal" as "maximized". That is to say, the conviction function $P(A)P(\neg B)/P(A, \neg B)$ attains its greatest value when $A \implies B$.

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