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  1. Ignite
  2. IGNITE-7438

LSQR: Sparse Equations and Least Squares for Lin Regression

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    Details

    • Type: New Feature
    • Status: Resolved
    • Priority: Major
    • Resolution: Done
    • Affects Version/s: None
    • Fix Version/s: 2.5
    • Component/s: ml
    • Labels:
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      Description

      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, 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 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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              • Assignee:
                dmitrievanthony Anton Dmitriev
                Reporter:
                chief Yury Babak
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                • Created:
                  Updated:
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