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.

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

Handle multimodal cases in maxent #635

Draft
wants to merge 1 commit into
base: main
Choose a base branch
from

Conversation

rohanbabbar04
Copy link
Contributor

@rohanbabbar04 rohanbabbar04 commented Jan 23, 2025

Description

  • Binomial

Checklist

  • Code style is correct (follows ruff and black guidelines)

@rohanbabbar04
Copy link
Contributor Author

rohanbabbar04 commented Jan 23, 2025

Some things to ask here:

  1. In some cases, the binomial distribution is bimodal. Should we focus on the major mode only?
image
  1. For bimodal or multimodal like we discussed is it fine to return a tuple of modes and handle it in optimize max ent.

What do you suggest @aloctavodia ?

@Advaitgaur004
Copy link

Advaitgaur004 commented Jan 23, 2025

I am adding a mode to other Python files, and I will make a pull request. is that fine @rohanbabbar04

@rohanbabbar04
Copy link
Contributor Author

rohanbabbar04 commented Jan 23, 2025

I am adding a mode to other Python files, and I will make a pull request. is that fine @rohanbabbar04

Sure, can you comment on #604 which ones are you working on so that we don't pick the same ones?

@codecov-commenter
Copy link

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 74.26%. Comparing base (f25da81) to head (6cb68cc).
Report is 93 commits behind head on main.

❗ There is a different number of reports uploaded between BASE (f25da81) and HEAD (6cb68cc). Click for more details.

HEAD has 1 upload less than BASE
Flag BASE (f25da81) HEAD (6cb68cc)
3 2
Additional details and impacted files
@@            Coverage Diff             @@
##             main     #635      +/-   ##
==========================================
- Coverage   82.23%   74.26%   -7.97%     
==========================================
  Files         101      105       +4     
  Lines        8020     8711     +691     
==========================================
- Hits         6595     6469     -126     
- Misses       1425     2242     +817     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

@Advaitgaur004
Copy link

I am adding a mode to other Python files, and I will make a pull request. is that fine @rohanbabbar04

Sure, can you comment on #604 which ones are you working on so that we don't pick the same ones?

Sure, you have already implemented Rice and Binomial, so I will drop this since I have already implemented it in my local setup.

@rohanbabbar04 rohanbabbar04 changed the title Add mode to Distributions Add mode to Distributions and handle multimodal cases Jan 23, 2025
@rohanbabbar04 rohanbabbar04 marked this pull request as draft January 23, 2025 19:33
@rohanbabbar04 rohanbabbar04 changed the title Add mode to Distributions and handle multimodal cases Handle multimodal cases in maxent Jan 23, 2025
@aloctavodia
Copy link
Contributor

Some things to ask here:

  1. In some cases, the binomial distribution is bimodal. Should we focus on the major mode only?
image 2. For bimodal or multimodal like we discussed is it fine to return a tuple of modes and handle it in optimize max ent.

What do you suggest @aloctavodia ?

Not sure, but probably better to return a tuple if more than one mode. And as a first approach allow to fix a single mode in maxent, but handle de case that the mode method could return a tuple

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

4 participants