[
https://issues.apache.org/jira/browse/SPARK-6386?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14617586#comment-14617586
]
Feynman Liang edited comment on SPARK-6386 at 7/7/15 10:59 PM:
---------------------------------------------------------------
Resolved by SPARK-8559
was (Author: fliang):
Closing since this is resolved by SPARK-8559
> add association rule mining algorithm to MLLib
> ----------------------------------------------
>
> Key: SPARK-6386
> URL: https://issues.apache.org/jira/browse/SPARK-6386
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Affects Versions: 1.3.0
> Reporter: zhangyouhua
>
> [~mengxr]
> association rule algorithm is find frequent items which are association，while
> given transition data set and minSupport and minConf. we can use FPGrowth
> algorithm mining frequent pattern item，but can not explain each other. so we
> should add association rule algorithm.
> for example：
> data set：
> A B C
> A C
> A D
> B E F
> minSupport :0.5
> minConf:0.5
> the frequent items-> support
> A ->0.75
> B ->0.5
> C ->0.5
> A C ->0.5
> use minSupport calculate minConf：
> A -> C: support {A C}/support {A} = 0.67
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
