Re: [jira] Commented: (MAHOUT-108) Implementation of Assoication Rules learning by Apriori algorithm

[Ted Dunning <te...@gmail.com>]

The Apriori algorithm has (I think) really bad scaling properties.  As such
I would suggest that the PFGrowth work by Robin pretty much takes the place
of Mahout-108.

On Sun, Sep 13, 2009 at 6:29 AM, Isabel Drost (JIRA) <ji...@apache.org>wrote:

>
>    [
> https://issues.apache.org/jira/browse/MAHOUT-108?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12754694#action_12754694]
>
> Isabel Drost commented on MAHOUT-108:
> -------------------------------------
>
> Contacted (at least tried to) Chao Deng asking for the status and if I
> could help him submit the patch. Should we close this issue as won't fix or
> defer it to a later version if he does not respond? Or is anyone else up to
> implementing a patch for this task until 0.2?
>
> > Implementation of Assoication Rules learning by Apriori algorithm
> > -----------------------------------------------------------------
> >
> >                 Key: MAHOUT-108
> >                 URL: https://issues.apache.org/jira/browse/MAHOUT-108
> >             Project: Mahout
> >          Issue Type: Task
> >         Environment: Linux, Hadoop-0.17.1
> >            Reporter: chao deng
> >             Fix For: 0.2
> >
> >   Original Estimate: 504h
> >  Remaining Estimate: 504h
> >
> > Target: Association Rules learning is a popular method for discovering
> interesting relations between variables in large databases. Here, we would
> implement the Apriori algorithm using Hadoop&Mapreduce parallel techniques.
> > Applications: Typically, association rules  learning is used to discover
> regularities between products in large scale transaction data in
> supermarkets. For example, the rule  "{onions, patatoes}->beef" found in the
> sales data would indicate that if a customer buys onions and potatoes
> together, he or she is likely to also buy beef. Such information can be used
> as the basis for decisions about marketing activities. In addition to the
> market basket analysis, association rules are employed today in many
> application areas including Web usage mining, intrusion detection and
> bioinformatics.
> > Apriori algorithm: Apriori is the best-known algorithm to mine
> association rules. It uses a breadth-first search strategy to counting the
> support of itemsets and uses a candidate generation function which exploits
> the downward closure property of support
>
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-- 
Ted Dunning, CTO
DeepDyve