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Posted to issues@spark.apache.org by "Marco Gaido (JIRA)" <ji...@apache.org> on 2018/08/24 09:50:00 UTC
[jira] [Updated] (SPARK-25219) KMeans Clustering - Text Data -
Results are incorrect
[ https://issues.apache.org/jira/browse/SPARK-25219?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Marco Gaido updated SPARK-25219:
--------------------------------
Component/s: (was: Spark Submit)
ML
> KMeans Clustering - Text Data - Results are incorrect
> -----------------------------------------------------
>
> Key: SPARK-25219
> URL: https://issues.apache.org/jira/browse/SPARK-25219
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 2.3.0
> Reporter: Vasanthkumar Velayudham
> Priority: Major
>
> Hello Everyone,
> I am facing issues with the usage of KMeans Clustering on my text data. When I apply clustering on my text data, after performing various transformations such as RegexTokenizer, Stopword Processing, HashingTF, IDF, generated clusters are not proper and one cluster is found to have lot of data points assigned to it.
> I am able to perform clustering with similar kind of processing and with the same attributes on the SKLearn KMeans algorithm.
> Upon searching in internet, I observe many have reported the same issue with KMeans clustering library of Spark.
> Request your help in fixing this issue.
> Please let me know if you require any additional details.
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