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It seems RLS is a way to reach the same solution as batch linear regression. It's probably more expensive than SGD, but is still interesting.
## Resources
- https://www.wikiwand.com/en/Recursive_lea…
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Rewrite this R implementation in efficient non-allocating .NET code https://gist.github.com/buybackoff/bfeb9c8959157dbf86310d383c93f00d
* [ ] Should return a structure with coefficients, the curr…
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https://en.wikipedia.org/wiki/Recursive_least_squares_filter
A Tutorial on Recursive methods in Linear Least Squares Problems
http://pfister.ee.duke.edu/courses/ece586/ex_proj_2008.pdf
Lect…
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Is there any particular reason why there is no capability for linear recursive least squares (RLS) in scipy? It is an absolute standard signal processing / data analysis algorithm, and I was somewhat …
e-pet updated
4 years ago
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This should reduce the amortized run-time by a factor proportional to L_train.
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Hi!
In some domains kernel recursive least squares algorithms are very useful. As well they are also evolving. One of the interesting evolutions is described in A novel extended kernel recursive le…
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**Is your feature request related to a problem? Please describe.**
Yes. I would request to add features for traditional system identification method like (recursive) least squares. In many cases, we …
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# High level description
Least squares batch filters and classical Kalman filters are both methods for estimating the state of a dynamic system from noisy measurements. They both use a mathematical…
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- [ ] Linear Systems Solvers - Dense General Matrices - simple driver `LAPACKE_?gesv`
- [ ] Least Square Systems solver - Dense General matrices - simple driver `LAPACKE_?gelsd` that does recursive SV…
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## Why
Execution effort needs to accurately map to actual resources used on transaction execution, otherwise we are not charging fees correctly.
## How will we measure success ?
[Computation Estim…