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.
Attachments
Issue Links
- Blocked
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IGNITE-7437 Partition based dataset implementation
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- Resolved
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- causes
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IGNITE-8268 Add documentation for linear regression (release 2.5)
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- Closed
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- links to
(1 links to)