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Local determination of nearest-nbrs: MI/CMI forest estimators with G-KSG (geodesic distance using Unsupervised forest) and Local Permutation #162

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SUKI-O opened this issue Nov 1, 2023 · 2 comments
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@SUKI-O
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SUKI-O commented Nov 1, 2023

Is your feature request related to a problem? Please describe.
Would like to get a Mutual Information / Conditional MI using geodesic distance derived from Unusupervised Forest as described in the following papers:

Describe the solution you'd like

  • experiment with the proposed algorithm(s) leveraging existing features in sktree and additional Python code
  • add/change Cython module(s) that will be needed for implementation
  • add tests to verify the results and performance

Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.

Additional context
Add any other context or screenshots about the feature request here.

@SUKI-O SUKI-O self-assigned this Nov 1, 2023
@icy-23
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icy-23 commented Nov 21, 2023

I'm interested in this, I also would be interested in general KL Divergence estimation

@SUKI-O SUKI-O mentioned this issue Nov 30, 2023
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@SUKI-O SUKI-O linked a pull request Nov 30, 2023 that will close this issue
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@adam2392 adam2392 changed the title MI/CMI forest estimators with G-KSG (geodesic distance using Unsupervised forest) Local determination of nearest-nbrs: MI/CMI forest estimators with G-KSG (geodesic distance using Unsupervised forest) and Local Permutation Mar 27, 2024
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3 participants