# What Is New in *genieclust*
## 1.1.0 (2022-09-05)
- [GENERAL] The cluster validity measures are discussed in more detail at
.
- [Python and R] New function:
`compare_partitions.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 (to the `cluster_validity` module in the Python version):
`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`.
- [BACKWARD INCOMPATIBILITY] `compare_partitions.normalized_confusion_matrix`
now solves the maximal assignment problem instead of applying
a primitive partial pivoting.
- [Python and R] New function: `compare_partitions.normalizing_permutation`
- [R] New function: `normalized_confusion_matrix`.
- [Python and R] New parameter to `compare_partitions.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] New function: `inequity.devergottini_index`.
- [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.