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From "Paritosh Ranjan (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (MAHOUT-1066) How to generate sparsed Vectors from the specified dictionary.
Date Mon, 08 Oct 2012 13:08:03 GMT

     [ https://issues.apache.org/jira/browse/MAHOUT-1066?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Paritosh Ranjan reassigned MAHOUT-1066:
---------------------------------------

    Assignee: Paritosh Ranjan
    
> How to generate sparsed Vectors from the specified dictionary.
> --------------------------------------------------------------
>
>                 Key: MAHOUT-1066
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-1066
>             Project: Mahout
>          Issue Type: Question
>          Components: Clustering
>    Affects Versions: 0.7
>            Reporter: Hiroaki Kubota
>            Assignee: Paritosh Ranjan
>
> I'd like to do clustering our natural language data.
> The first, I used the 'seq2sparse' command to vectorize our data.
> I got sparsed vectors and a dictionary.
> And we could do k-means and got suitable clusters.
> It was OK.
> The next, I'd like to add some data to previous calculated clusters.
> So I want to get additional vectors from new additional data based on previous dictionary.
> Probably I think,
> It is impossible to get really accurate vectors by using only additional data.
> However,I'd like to reduce processing time so It's OK if I get the vector that is useful
for decision tree.
> Please give me advice !
> Regard,

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