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From "Ignite TC Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (IGNITE-9978) [ML] Implement Compound Naive Bayes classifier
Date Sat, 01 Jun 2019 00:36:00 GMT

    [ https://issues.apache.org/jira/browse/IGNITE-9978?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16853506#comment-16853506
] 

Ignite TC Bot commented on IGNITE-9978:
---------------------------------------

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{color:#d04437}PDS 4{color} [[tests 0 TIMEOUT , Exit Code |https://ci.ignite.apache.org/viewLog.html?buildId=4003698]]

{color:#d04437}Scala (Visor Console){color} [[tests 0 Exit Code |https://ci.ignite.apache.org/viewLog.html?buildId=4003650]]

{color:#d04437}Platform .NET (Inspections)*{color} [[tests 0 Failure on metric |https://ci.ignite.apache.org/viewLog.html?buildId=4003701]]

{color:#d04437}Client Nodes{color} [[tests 0 Exit Code |https://ci.ignite.apache.org/viewLog.html?buildId=4003619]]

{color:#d04437}[Licenses Headers]{color} [[tests 0 Exit Code |https://ci.ignite.apache.org/viewLog.html?buildId=4003665]]

{panel}
[TeamCity *--&gt; Run :: All* Results|https://ci.ignite.apache.org/viewLog.html?buildId=4003728&amp;buildTypeId=IgniteTests24Java8_RunAll]

> [ML] Implement Compound Naive Bayes classifier
> ----------------------------------------------
>
>                 Key: IGNITE-9978
>                 URL: https://issues.apache.org/jira/browse/IGNITE-9978
>             Project: Ignite
>          Issue Type: Task
>          Components: ml
>            Reporter: Alexey Platonov
>            Assignee: Ravil Galeyev
>            Priority: Major
>              Labels: new-feature
>             Fix For: 2.8
>
>          Time Spent: 10m
>  Remaining Estimate: 0h
>
> We need to create compound Naive Bayes classifier as model composition of several Naive
Bayes classifiers where each classifier represents subset of features of one type. For example
such model may contain Naive Bayes model over Gauss Distribution for all continuous features
and Naive Bayes model over Discrete Distribution for enum-like features.



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