Roman Feldbauer

18 isn't particularly high, but we've seen datasets, where this came with high hubness (see e.g. p. 2885/6 of [this previous paper](http://www.cp.jku.at/people/schedl/Research/Publications/pdf/schnitzer_jmlr_2012.pdf). I am not aware of research directly linking...

I assume you want to compare the two methods with respect to your classification task? In this case, I would approach this exactly the way you suggested. Simply create two...

These are known issues of an old scikit-learn version when used with newer numpy versions. They do not cause any errors and you may ignore them, or even filter them...

A note of caution first, v0.30 is experimental at this point and might have all kinds of problems as is. If you still want to try it, I suggest creating...

Can you please try without the `[ann]` part in the end? Perhaps this does not work when installing directly from github. The difference would only be whether other packages like...

From v0.30 scikit-hubness does provide an own implementation of KNeighborsClassifier anymore. Instead, you can use the one from scikit-learn. The workflow will be as outline [here](https://scikit-learn.org/stable/modules/neighbors.html#nearest-neighbors-transformer). For example, you can...

I would in this case suggest you stick with the old scikit-hubness version for the time being, because I don't really have any tested example code for the new version...

Yes, this should work.

`puffinn` (note the double-n) is not available from PyPI. `puffin` is an unrelated package. Did you get any warnings/error messages from following the manual puffinn installation steps? If no, did...

I only now realized you are on Windows. Unfortunately, `falconn` does not support Windows, and neither does `puffinn`. So LSH is only available on Linux or Macos.