[jira] Resolved: (MAHOUT-521) Add option to DictionaryVectorizer to create (tf and tfidf) vectors on-the-fly using a given dictionary

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

     [ https://issues.apache.org/jira/browse/MAHOUT-521?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved MAHOUT-521.
------------------------------

    Resolution: Fixed

Per Ted, punting whatever may remain in this issue to a future JIRA ticket, for 0.5.

> Add option to DictionaryVectorizer to create (tf and tfidf) vectors on-the-fly using a given dictionary 
> --------------------------------------------------------------------------------------------------------
>
>                 Key: MAHOUT-521
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-521
>             Project: Mahout
>          Issue Type: New Feature
>            Reporter: Robin Anil
>            Assignee: Robin Anil
>             Fix For: 0.4
>
>         Attachments: MAHOUT-521.patch, MAHOUT-move-encoder.patch, MAHOUT-vectorizer-move.patch, MAHOUT-vectorizer-move.patch
>
>
> Current dictionary vectorizer takes a set of text-files, creates the dictionary and convert them to text vectors. In a classification scenario, the vectorizer needs to take a Already existing dictionary and use the ids to convert text to vectors and optionally do the following
> 1. Choose between tf|tfidf weights (need to take the document frequency as an input for this)
> 2. Add new words to the dictionary and provide options to write it to the disk and read it back
> 3. Add option to normalize/lognormalize 
>  

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