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

[ENH] Implement the Proximity Forest classifier using aeon distances #159

Closed
TonyBagnall opened this issue Mar 6, 2023 · 0 comments · Fixed by #1729
Closed

[ENH] Implement the Proximity Forest classifier using aeon distances #159

TonyBagnall opened this issue Mar 6, 2023 · 0 comments · Fixed by #1729
Labels
classification Classification package distances Distances package enhancement New feature, improvement request or other non-bug code enhancement implementing algorithms Implementing new algorithms/estimators

Comments

@TonyBagnall
Copy link
Contributor

Is your feature request related to a problem? Please describe.

Proximity Forest is a distance based ensemble of decision trees. We do not currently have a working version of PF in aeon, but would very much like to have one. This is moderately complicated

https://link.springer.com/article/10.1007/s10618-019-00617-3
https://arxiv.org/abs/1808.10594

The original java version is here
https://github.com/benjaminmlucas/proximity-forest

We have a java version here
https://github.com/time-series-machine-learning/tsml-java/blob/master/src/main/java/tsml/classifiers/distance_based/proximity/ProximityForest.java

There is a version in the old repo, but it is broken and uses dataframes
https://github.com/sktime/sktime/blob/main/sktime/classification/distance_based/_proximity_forest.py

Describe the solution you'd like
I would like an implementation optimised for speed, that uses our distance functions and that can achieve accuracy results that are not significantly different to those published

Additional context
We would be happy to help the development and test performance against other implementations.

@TonyBagnall TonyBagnall added enhancement New feature, improvement request or other non-bug code enhancement classification Classification package implementing algorithms Implementing new algorithms/estimators labels Mar 6, 2023
@TonyBagnall TonyBagnall changed the title [ENH] Proximity Forest implementation using numpy [ENH] Implement the Proximity Forest implementation using numpy Mar 8, 2023
@TonyBagnall TonyBagnall changed the title [ENH] Implement the Proximity Forest implementation using numpy [ENH] Implement the Proximity Forest classifier using numpy Mar 10, 2023
@TonyBagnall TonyBagnall added the distances Distances package label May 13, 2023
@TonyBagnall TonyBagnall changed the title [ENH] Implement the Proximity Forest classifier using numpy [ENH] Implement the Proximity Forest classifier using aeon distances May 13, 2023
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
classification Classification package distances Distances package enhancement New feature, improvement request or other non-bug code enhancement implementing algorithms Implementing new algorithms/estimators
Projects
None yet
Development

Successfully merging a pull request may close this issue.

1 participant