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From Konstantinos Patsakis <>
Subject Re: FP-Growth question
Date Mon, 13 May 2013 11:18:43 GMT

thank you for the feedback. Unfortunately I do not have any ready log to post.

I am trying to extend Mahout library with another MapReduce step to compute the association
I can form the association rules from Mahout's output, but I cannot compute the interestingness
measures such as confidence.

For instance, let's say that we have a frequent pattern as output [a,b,c,d,e]. We already
know the pattern's support. The idea is to form a rule by removing one item and put it at
the right part of a rule, for example: abcd->e .

The confidence measure is computed by dividing the support of the [abcde] item set that we
already know by the support of the item set [abcd] which is the right part of the rule. But
we do not have this information because the item set [abcd] may not even be a frequent one
and it is not feasible to search all the patterns for the computation of one association rule.

Any suggestions are more than welcome.

Thank you in advance,
On May 13, 2013, at 12:48 PM, Louis Hénault <> wrote:

> Hi,
> After using FPG within Mahout, you get raw results like this:
> Key: i: Value: ([i],K1), ([i, j],K2), ([l, i],K3), etc...
> This means that for the key i, the top associations with i are first i
> in K1 transactions, then i and j appears in K2 transactions, etc...
> with K1 > K2 > K3 > ...
> Then, you have to use the raw results to measure your associations
> rules. You can use several metrics, e.g conviction measure (see
> ).
> I hope it helped,
> Louis
> 2013/5/13 Konstantinos Patsakis <>
>> Hello,
>> I am using Mahout's FP-Growth algorithm an I would like to extract
>> association rules after the frequent pattern mining.
>> However, I am experiencing some difficulties because I do not know how to
>> manipulate the output of Mahout to generate association rules. Maybe you
>> could help me with this or you need more info about my obstacles?
>> Thank you in advance,
>> Konstantinos

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