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From "Anton Dmitriev (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (IGNITE-7438) LSQR: Sparse Equations and Least Squares for Lin Regression
Date Fri, 09 Feb 2018 09:15:00 GMT

     [ https://issues.apache.org/jira/browse/IGNITE-7438?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Anton Dmitriev updated IGNITE-7438:
-----------------------------------
    Description: 
This task consists of two parts:
 * Implementation of the LSQR iterative solver for systems of linear equations.
 * Implementation of the LSQR-based linear regression trainer.

Apache Ignite LSQR iterative solver is based on [SciPy reference implementation|[https://github.com/scipy/scipy/blob/master/scipy/sparse/linalg/isolve/lsqr.py#L98]|https://github.com/scipy/scipy/blob/master/scipy/sparse/linalg/isolve/lsqr.py#L98].],
but it's distributed and can efficiently work in cases when a data is distributed across
a cluster. Distribution is achieved as result of changing bi

  was:
This task consists of two parts:
 * Implementation of the LSQR iterative solver for systems of linear equations.
 * Implementation of the LSQR-based linear regression trainer.

LSQR iterative solver is implemented using SciPy reference implementation.


> LSQR: Sparse Equations and Least Squares for Lin Regression
> -----------------------------------------------------------
>
>                 Key: IGNITE-7438
>                 URL: https://issues.apache.org/jira/browse/IGNITE-7438
>             Project: Ignite
>          Issue Type: New Feature
>          Components: ml
>            Reporter: Yury Babak
>            Assignee: Anton Dmitriev
>            Priority: Major
>
> This task consists of two parts:
>  * Implementation of the LSQR iterative solver for systems of linear equations.
>  * Implementation of the LSQR-based linear regression trainer.
> Apache Ignite LSQR iterative solver is based on [SciPy reference implementation|[https://github.com/scipy/scipy/blob/master/scipy/sparse/linalg/isolve/lsqr.py#L98]|https://github.com/scipy/scipy/blob/master/scipy/sparse/linalg/isolve/lsqr.py#L98].],
but it's distributed and can efficiently work in cases when a data is distributed across
a cluster. Distribution is achieved as result of changing bi



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