[jira] [Commented] (OPENNLP-861) Add Chi-Squared Data Indexer for Feature Selection

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

    [ https://issues.apache.org/jira/browse/OPENNLP-861?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15437779#comment-15437779 ] 

Joey Hong commented on OPENNLP-861:
-----------------------------------

I have been using one, which extends the AbstractDataIndexer class for a current project I am doing using OpenNLP. I just need to do a few adaptations before it is ready to be pushed to OpenNLP.

> Add Chi-Squared Data Indexer for Feature Selection
> --------------------------------------------------
>
>                 Key: OPENNLP-861
>                 URL: https://issues.apache.org/jira/browse/OPENNLP-861
>             Project: OpenNLP
>          Issue Type: New Feature
>          Components: Machine Learning
>    Affects Versions: 1.6.0
>            Reporter: Joey Hong
>            Priority: Minor
>              Labels: features
>             Fix For: 1.6.1
>
>
> Text classification will naturally produce a lot of features. A lot of them are independent of the category, and provide no real information gain in the classification.
> The Chi-Squared feature selection method will allow features that do not pass a threshold for dependency to be removed from the feature list, keeping the feature list a reasonable size without significantly affecting the classification accuracy.



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