# Changelog ## 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 (as per the major revision of ): `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 will be provided in a forthcoming paper; see . ## 1.1.3 (2023-01-17) * [R] `mst.default` now throws an error if any element in the input matrix is missing/infinite. * [Python] Fixed the call to `mlpack.emst` that stopped working with the new version of `mlpack`. ## 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](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 . * [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](https://doi.org/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.