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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (IGNITE-6880) KNN(k nearest neighbor) algorithm
Date Thu, 30 Nov 2017 11:40:00 GMT

    [ https://issues.apache.org/jira/browse/IGNITE-6880?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16272554#comment-16272554

ASF GitHub Bot commented on IGNITE-6880:

GitHub user zaleslaw opened a pull request:


    IGNITE-6880: KNN Regression and Classification

    Also added Labeled Dataset and loading from txt file

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

    $ git pull https://github.com/gridgain/apache-ignite ignite-6880

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


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

    This closes #3117
commit 2cb4f5f3da67ad077f837eeeda11baf44c101245
Author: zaleslaw <zaleslaw.sin@gmail.com>
Date:   2017-11-14T12:47:29Z

    Refactored keys

commit 462719fef2364cd2aded23bb32edf4d0a53b9d7f
Author: zaleslaw <zaleslaw.sin@gmail.com>
Date:   2017-11-14T12:47:51Z

    Added tests

commit c180c8c60a1b43a516cd7a045420bc1dc16adcdd
Author: zaleslaw <zaleslaw.sin@gmail.com>
Date:   2017-11-14T12:48:14Z

    Added vectors

commit 39766ed0bfdb9a95118b7e0c59ec39a441307c0e
Author: zaleslaw <zaleslaw.sin@gmail.com>
Date:   2017-11-14T12:48:43Z

    Refactored storages and matrices

commit b9deec6d3f71db8da45800ad8a6f0ec560a25294
Author: zaleslaw <zaleslaw.sin@gmail.com>
Date:   2017-11-14T12:49:11Z

    Fixed issues with keys

commit 3dbbb20efccbc85bf8022b34935096d5310c9554
Author: zaleslaw <zaleslaw.sin@gmail.com>
Date:   2017-11-14T18:25:14Z

    Added kNN classifier draft

commit 41ee88add4ebc31efa7a4e903ff4d78d92bd2e8a
Author: zaleslaw <zaleslaw.sin@gmail.com>
Date:   2017-11-15T16:59:44Z

    Added loading from file

commit 68c82c7f3ac3c220f52f76ce0057032bc55b33fe
Author: zaleslaw <zaleslaw.sin@gmail.com>
Date:   2017-11-15T18:56:48Z

    Added kNN regression draft

commit 552d9af6d9ec0ca5156a7b84457c93dc896946e3
Author: zaleslaw <zaleslaw.sin@gmail.com>
Date:   2017-11-16T11:28:41Z

    Added different distances

commit a003cc22902afa2fdfcb1d90a29d07ff936a13be
Author: Zinoviev Alexey <zaleslaw.sin@gmail.com>
Date:   2017-11-21T16:32:25Z

    Fix codestyle

commit 29014354df79f2ff6e46542420030c0f091566fc
Author: Zinoviev Alexey <zaleslaw.sin@gmail.com>
Date:   2017-11-26T14:01:39Z

    Merge branch 'master' into ignite-6880

commit 12f081969baa25c49b0c55f74e3551c113ebb8d8
Author: Zinoviev Alexey <zaleslaw.sin@gmail.com>
Date:   2017-11-26T15:17:25Z

    Added distances and test for them

commit 8a1cc76ed63c4d72a76af37423d8a197eafd6f31
Author: Zinoviev Alexey <zaleslaw.sin@gmail.com>
Date:   2017-11-27T15:44:41Z

    Added LabeledDataset

commit 754208280ee929df8c317eb15c0a3071a63dc6f5
Author: Zinoviev Alexey <zaleslaw.sin@gmail.com>
Date:   2017-11-28T15:34:01Z

    Added tests

commit c5c37304929d67aa9722d701d9b40b976198b812
Author: Zinoviev Alexey <zaleslaw.sin@gmail.com>
Date:   2017-11-28T15:52:53Z

    Added tests

commit d282042fb4625159f65629fe1a9efa0e25831195
Author: Zinoviev Alexey <zaleslaw.sin@gmail.com>
Date:   2017-11-28T16:29:27Z

    Added normalization

commit 52749bc9bcfe2d9ad50b92b0f392e2baa4a505f1
Author: Zinoviev Alexey <zaleslaw.sin@gmail.com>
Date:   2017-11-29T16:04:05Z

    Added code style

commit ed78a89cf59d07de2781c755749ea97e041f8839
Author: Zinoviev Alexey <zaleslaw.sin@gmail.com>
Date:   2017-11-30T11:30:07Z

    Added code style

commit 663a8e1a1ea875cfa8e7b31652a7aa7ec1acd668
Author: Zinoviev Alexey <zaleslaw.sin@gmail.com>
Date:   2017-11-30T11:36:08Z

    Added code style


> KNN(k nearest neighbor) algorithm
> ---------------------------------
>                 Key: IGNITE-6880
>                 URL: https://issues.apache.org/jira/browse/IGNITE-6880
>             Project: Ignite
>          Issue Type: New Feature
>          Components: ml
>            Reporter: Yury Babak
>            Assignee: Aleksey Zinoviev
> We want to add KNN to Apache Ignite ML module.
> Our implementation should support two modes:
> * KNN-classifier(in this mode the output is a class membership. An object is classified
by a majority vote of its neighbors, with the object being assigned to the class most common
among its k nearest neighbors (k is a positive integer, typically small). If k = 1, then the
object is simply assigned to the class of that single nearest neighbor)
> * KNN-regression(the output is the property value for the object. This value is the average
of the values of its k nearest neighbors.)

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