# Changelog¶

## 1.1.6 (2024-08-22)¶

[PYTHON] The package now works with

*numpy*2.0.

## 1.1.5 (2023-10-18)¶

[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.

## 1.1.4 (2023-03-31)¶

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

## 1.1.3 (2023-01-17)¶

[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.

## 1.1.2 (2022-09-17)¶

[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.

## 1.1.1 (2022-09-15)¶

[Python] #75:

`nmslib`

is now optional.[BUILD TIME]: The use of

`ssize_t`

was not portable.

## 1.1.0 (2022-09-05)¶

[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; see our (GitHub-only) 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`

.

## 1.0.1 (2022-08-08)¶

[GENERAL] A paper on the

`genieclust`

package is now available: M. Gagolewski, genieclust: Fast and robust hierarchical clustering, SoftwareX 15, 100722, 2021, DOI: 10.1016/j.softx.2021.100722.[Python]

`plots.plot_scatter`

now uses a more accessible default palette (from R 4.0.0).[Python and R] New function:

`devergottini_index`

.

## 1.0.0 (2021-04-22)¶

[R] Use

`mlpack`

instead of`RcppMLPACK`

(#72). This package is merely suggested, not dependent upon.

## 0.9.8 (2021-01-08)¶

[Python] Require Python >= 3.7 (implied by

`numpy`

).[Python] Require

`nmslib`

.[R] Use

`RcppMLPACK`

directly; remove dependency on`emstreeR`

.[R] Use

`tinytest`

for unit testing instead of`testthat`

.

## 0.9.4 (2020-07-31)¶

[BUGFIX] [R] Fix build errors on Solaris.

## 0.9.3 (2020-07-25)¶

[BUGFIX] [Python] Add code coverage CI. Fix some minor inconsistencies. Automate the

`bdist`

build chain.[R] Update DESCRIPTION to meet the CRAN policies.

## 0.9.2 (2020-07-22)¶

[BUGFIX] [Python] Fix broken build script for OS X with no OpenMP.

## 0.9.1 (2020-07-18)¶

[GENERAL] The package has been completely rewritten. The core functionality is now implemented in C++ (with OpenMP).

[GENERAL] Clustering with respect to HDBSCAN*-like mutual reachability distances is supported.

[GENERAL] The parallelised Jarnik-Prim algorithm now supports on-the-fly distance computations. Euclidean minimum spanning tree can be determined with

`mlpack`

, which is much faster in low-dimensional spaces.[R] R version is now available.

[Python] [Experimental] The GIc algorithm proposed by Anna Cena in her 2018 PhD thesis is added.

[Python] Approximate version based on nearest neighbour graphs produced by

`nmslib`

is added.

## 0.1a2 (2018-05-23)¶

[Python] Initial PyPI release.