Genieclust

* [PYTHON] The package now works with *numpy* 2.0.

* [BACKWARD INCOMPATIBILITY] [Python and R] Inequality measures
are no longer referred to as inequity measures.

* [BACKWARD INCOMPATIBILITY] [Python and R]
Some external cluster validity measures were renamed:
`adjusted_asymmetric_accuracy` -> `normalized_clustering_accuracy`,
`normalized_accuracy` -> `normalized_pivoted_accuracy`.

* [BACKWARD INCOMPATIBILITY] [Python] `compare_partitions2` has been removed,
as `compare_partitions` and other partition similarity scores
now support both pairs of label vectors `(x, y)` and confusion matrices
`(x=C, y=None)`.

* [Python and R] New parameter to `pair_sets_index`: `clipped`.

* In `normalizing_permutation` and external cluster validity measures,
the input matrices can now be of the type `double`.

* [BUGFIX] [Python] 80: Fixed adjustment for `nmslib_n_neighbors`
in small samples.

* [BUGFIX] [Python] 82: `cluster_validity` submodule not imported.

* [BUGFIX] Some external cluster validity measures
now handle NaNs better and are slightly less prone to round-off errors.

* [Python] The GIc algorithm is no longer marked as experimental;
its description is provided in
<https://doi.org/10.1007/s00357-024-09483-1>.

* [R] `mst.default` now throws an error if any element in the input matrix
is missing/infinite.

* [Python] The call to `mlpack.emst` that stopped working
with the new version of `mlpack` has been fixed.

* [Python and R] `adjusted_asymmetric_accuracy`
now accepts confusion matrices with fewer columns than rows.
Such "missing" columns are now treated as if they were filled with 0s.

* [Python and R] `pair_sets_index`, and `normalized_accuracy` return
the same results for non-symmetric confusion matrices and transposes thereof.

* [Python] 75: `nmslib` is now optional.

* [BUILD TIME]: The use of `ssize_t` was not portable.