* [Python and R] New function: `adjusted_asymmetric_accuracy`.
* [Python and R] Implementations of the so-called internal cluster
validity measures discussed in
DOI: [10.1016/j.ins.2021.10.004](https://doi.org/10.1016/j.ins.2021.10.004);
see our (GitHub-only) [CVI](https://github.com/gagolews/optim_cvi) package
for R. In particular, the generalised Dunn indices are based on the code
originally authored by Maciej Bartoszuk. Thanks.
Functions added (`cluster_validity` module):
`calinski_harabasz_index`,
`dunnowa_index`,
`generalised_dunn_index`,
`negated_ball_hall_index`,
`negated_davies_bouldin_index`,
`negated_wcss_index`,
`silhouette_index`,
`silhouette_w_index`,
`wcnn_index`.
These cluster validity measures are discussed
in more detail at <https://clustering-benchmarks.gagolewski.com/>.
* [BACKWARD INCOMPATIBILITY] `normalized_confusion_matrix`
now solves the maximal assignment problem instead of applying
the somewhat primitive partial pivoting.
* [Python and R] New function: `normalizing_permutation`
* [R] New function: `normalized_confusion_matrix`.
* [Python and R] New parameter to `pair_sets_index`: `simplified`.
* [Python] New parameters to `plots.plot_scatter`:
`axis`, `title`, `xlabel`, `ylabel`, `xlim`, `ylim`.