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https://issues.apache.org/jira/browse/SPARK-4001?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14177643#comment-14177643
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Jacky Li commented on SPARK-4001:
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Maybe there is a misunderstand, I do not mean to use it in database by saying
"transactional data set".
Apriori is the classic algorithm for freq-item mining, and the frequent item
sets determined by Apriori can be used to determine association rules which
highlight general trends in the data set. This has applications in domains such
as market basket analysis for cross-selling and up-selling.
I am not sure whether there is a freq-item algorithm in the mllib, so actually
I am implementing Apriori and FP-Growth (not include in this JIRA thread). Will
it be useful if contribute to mllib?
> Add Apriori algorithm to Spark MLlib
> ------------------------------------
>
> Key: SPARK-4001
> URL: https://issues.apache.org/jira/browse/SPARK-4001
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Jacky Li
> Assignee: Jacky Li
>
> Apriori is the classic algorithm for frequent item set mining in a
> transactional data set. It will be useful if Apriori algorithm is added to
> MLLib in Spark
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