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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 09:29:00 GMT

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

Anton Dmitriev updated IGNITE-7438:
    Fix Version/s: 2.5

> 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|http://example.com/],
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 LSQR solver to solve system
of linear equations which represents linear regression problem.

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