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[ENH] Implement Proximity Forest 2.0 classifier using aeon distances #1978

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@itsdivya1309 itsdivya1309 commented Aug 15, 2024

Reference Issues/PRs

Closes: #428
Incorporates changes suggested in #1874 (maybe we can close PR #1876)

What does this implement/fix? Explain your changes.

  1. Created a private distance file to parameterise DTW and ADTW distances.
  2. Created a function to calculate the first_order_derivative of a time series.
  3. Implemented the ProximityTree2 and ProximityForest2 class, as per the paper.
  4. Added the classes to API.
  5. Wrote unit tests.

To do:

  • Improve the computational efficiency by implementing Early Abandoning and Pruning algorithm for elastic distance measures.

@aeon-actions-bot aeon-actions-bot bot added classification Classification package enhancement New feature, improvement request or other non-bug code enhancement labels Aug 15, 2024
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Thank you for contributing to aeon

I have added the following labels to this PR based on the title: [ $\color{#FEF1BE}{\textsf{enhancement}}$ ].
I have added the following labels to this PR based on the changes made: [ $\color{#BCAE15}{\textsf{classification}}$ ]. Feel free to change these if they do not properly represent the PR.

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I would put the distances in the same file as pf2 for now

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have we compared results vs published?

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MatthewMiddlehurst commented Sep 16, 2024

Not yet, need to put it on the cluster. I have not got results for the original yet also.

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have we compared results vs published?

Actually, the algorithm isn't complete yet. We still need to work on computational power, particularly integrating the EAP technique. I'd resume the work in a couple of days.

@MatthewMiddlehurst MatthewMiddlehurst marked this pull request as draft September 21, 2024 13:05
@itsdivya1309 itsdivya1309 marked this pull request as ready for review October 28, 2024 05:08
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Want to run this soon. This is not blocking that, but some component seems to be non-deterministic.

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[ENH] Implement the Proximity Forest 2 classifier using aeon distances
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