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https://issues.apache.org/jira/browse/IGNITE-7438?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16358278#comment-16358278
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ASF GitHub Bot commented on IGNITE-7438:
----------------------------------------

Github user asfgit closed the pull request at:

    https://github.com/apache/ignite/pull/3494


> 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
>             Fix For: 2.5
>
>
> This task consists of two parts:
>  * Implementation of the +LSQR iterative solver+ of 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],
>  but it's distributed and can:
>  * Efficiently work in cases when a data is distributed across a cluster. 
>  * Utilize all CPU resources by processing different parts of data on 
> different cores.  
> These advantages are achieved as result of changing [Golub-Kahan-Lanczos 
> Bidiagonalization 
> Procedure|http://www.netlib.org/utk/people/JackDongarra/etemplates/node198.html]
>  procedure which is a core of LSQR algorithm and utilizing features of 
> Partition Based Dataset implementation.
>  
> LSQR-based linear regression trainer is a trainer that uses the LSQR solver 
> to solve a system of linear equations which represents a linear regression 
> problem.



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