[ENH] Implement the Proximity Forest classifier using aeon distances #159
Labels
classification
Classification package
distances
Distances package
enhancement
New feature, improvement request or other non-bug code enhancement
implementing algorithms
Implementing new algorithms/estimators
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.
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