Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Online learning for model #126

Open
jasonmcewen opened this issue May 20, 2020 · 1 comment
Open

Online learning for model #126

jasonmcewen opened this issue May 20, 2020 · 1 comment
Labels
enhancement New feature or request future release Will be worked on for a release that is not the next one
Projects
Harmonic

Comments

@jasonmcewen
Copy link
Contributor

jasonmcewen commented May 20, 2020 •
edited

In high dimensions, storing all of the samples to fit a model can require a lot of RAM. This could be avoiding by switching to an online learning algorithm for model fitting.
@jasonmcewen jasonmcewen created this issue from a note in Harmonic (Icebox) May 20, 2020
@jasonmcewen jasonmcewen moved this from Icebox to Ice in Harmonic Jul 15, 2020
@mmdocherty mmdocherty added the enhancement New feature or request label Jul 27, 2022
@mmdocherty
Copy link
Collaborator

Further to this, this could be linked to using NF to draw more samples from the posterior for fitting rather than train/test chain split - will discuss this later after more pressing releases

@mmdocherty mmdocherty added the future release Will be worked on for a release that is not the next one label Jul 27, 2022
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
enhancement New feature or request future release Will be worked on for a release that is not the next one
Projects
Harmonic
  
Ice Box
Milestone
No milestone
Development

No branches or pull requests
2 participants
@jasonmcewen @mmdocherty