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It would be great to support more distance metrics, especially some which cannot be emulated by pre/post-processing of the data.
- [x] Manhattan metric ()
- [x] Chebyshev metric (), useful for many …
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## Goal
We want to make a simulation study script that can be easily parallelizable.
## Context
For this simulation study we want to vary the number of central Rt curves for different situati…
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I've had this notebook running for about an hour and it's still not done. It has been stuck on the second cell in section '4) Repeating the above, this time with ZTF + WISE manifold' for most of the t…
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Euclidean, Manhattan, Minkowski, cosine similarity
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This is a neat polars plug in. Thanks! Do you have plans for implementing the Ball Tree algorithm like in scikit-learn?
https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.BallTree.h…
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This is a meta-issue tracking support for Apple Health metrics. It includes both metrics that are already supported, along with those which have been requested.
## Metrics
### Activity
- [X] Ac…
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- test: `tests/unit/preprocessor/_compare_with_refs/test_compare_with_refs.py`
- test result: when an all-masked array is used as data input, `distance_metric` returns data element 0 instead of `mask…
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### Problem
Measuring distances on the map requires a scale. This is present in principle in the bottom corner given both in metric and imperial units. However, I find it way too small to be useful.
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Is it possible to use distance metric weighting if using l1, l2, or p norm ?
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I think it would be nice to add a standard implementation of the Hausdorff distance in Ignite as a `Metric`.