[jira] [Commented] (SPARK-21244) KMeans applied to processed text day clumps almost all documents into one cluster

["Nassir (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-21244?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16071447#comment-16071447 ] 

Nassir commented on SPARK-21244:
--------------------------------

Hi, 

The pyspark k-means implementation is on the same 20 newsgroup document set that sklearn k-means is run on. 

pyspark version does not produce any meaningful clsuters, unlike the sklearn k-means (both using euclidean distance as a distance measure).

The 'bug' is that pyspark k-means applied to tf-idf documents does not provide expected results. I would be interested to know if anyone has used k-means in spark mllib to cluster a standard document set such as the 20 news group set? Do you get almost all the documents clump into one cluster as I do?

> KMeans applied to processed text day clumps almost all documents into one cluster
> ---------------------------------------------------------------------------------
>
>                 Key: SPARK-21244
>                 URL: https://issues.apache.org/jira/browse/SPARK-21244
>             Project: Spark
>          Issue Type: Bug
>          Components: ML
>    Affects Versions: 2.1.1
>            Reporter: Nassir
>
> I have observed this problem for quite a while now regarding the implementation of pyspark KMeans on text documents - to cluster documents according to their TF-IDF vectors. The pyspark implementation - even on standard datasets - clusters almost all of the documents into one cluster. 
> I implemented K-means on the same dataset with same parameters using SKlearn library, and this clusters the documents very well. 
> I recommend anyone who is able to test the pyspark implementation of KMeans on text documents - which obviously has a bug in it somewhere.
> (currently I am convert my spark dataframe to pandas dataframe and running k means and converting back. However, this is of course not a parallel solution capable of handling huge amounts of data in future)
> Here is a link to the question i posted a while back on stackoverlfow: https://stackoverflow.com/questions/43863373/tf-idf-document-clustering-with-k-means-in-apache-spark-putting-points-into-one



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