[jira] [Commented] (SOLR-9186) Logistic regression modeling for text

["Cao Manh Dat (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SOLR-9186?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15319613#comment-15319613 ] 

Cao Manh Dat commented on SOLR-9186:
------------------------------------

It would be interesting idea. I just have some questions:
- Do we classify based on one or many fields?
- To represent doc -> vector, should we use tf-idf or just tf? So the field must have termvector stored?


> Logistic regression modeling for text
> -------------------------------------
>
>                 Key: SOLR-9186
>                 URL: https://issues.apache.org/jira/browse/SOLR-9186
>             Project: Solr
>          Issue Type: New Feature
>            Reporter: Joel Bernstein
>            Assignee: Joel Bernstein
>
> SOLR-8492 optimizes a logistic regression model for numeric fields. While this is interesting, I think it would be more interesting to build logistic regression models on text within an inverted index.
> This ticket will use the same *parallel iterative framework* as SOLR-8492, but different data access patterns on the shards, to optimize a logistic regression model on text.
> This will support use cases such as building models for spam detection, sentiment analysis and threat detection.



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