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Posted to issues@ignite.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2018/08/06 12:31:00 UTC

[jira] [Commented] (IGNITE-9065) Gradient boosting optimization

    [ https://issues.apache.org/jira/browse/IGNITE-9065?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16570150#comment-16570150 ] 

ASF GitHub Bot commented on IGNITE-9065:
----------------------------------------

GitHub user avplatonov opened a pull request:

    https://github.com/apache/ignite/pull/4486

    IGNITE-9065: Indexes integration for GDB

    

You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/gridgain/apache-ignite IGNITE-9065

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/ignite/pull/4486.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #4486
    
----
commit e85afb7391ae9c189606685c1bdd73749ff761c9
Author: Alexey Platonov <ap...@...>
Date:   2018-08-03T16:30:38Z

    init comit

commit bf515c5feb1d4e1de46c25a0d3e6a99edc142c72
Author: Alexey Platonov <ap...@...>
Date:   2018-08-06T12:05:55Z

    indexes reusing for gradient boosting

commit 415edd5036e323af974e44b7669bbb7ea3dc7b60
Author: Alexey Platonov <ap...@...>
Date:   2018-08-06T12:08:29Z

    Merge branch 'master' of https://github.com/apache/ignite into IGNITE-9065

commit 2a6f461b6add763ce5e4b7e8d063a53dc2dc2293
Author: Alexey Platonov <ap...@...>
Date:   2018-08-06T12:26:21Z

    delete useless generics

----


> Gradient boosting optimization
> ------------------------------
>
>                 Key: IGNITE-9065
>                 URL: https://issues.apache.org/jira/browse/IGNITE-9065
>             Project: Ignite
>          Issue Type: Improvement
>          Components: ml
>            Reporter: Yury Babak
>            Assignee: Alexey Platonov
>            Priority: Major
>             Fix For: 2.7
>
>
> We need to optimize GDB learning by reusing same index for learning decision trees.



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