Genieclust Versions Save

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 https://doi.org/10.48550/arXiv.2209.02935): 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.

1.1.3 (2023-01-17)

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

• [Python] Fixed call to mlpack.emst that no longer worked 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)

• [GENERAL] The cluster validity measures are discussed in more detail at https://clustering-benchmarks.gagolewski.com.

• [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; 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 (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.

genieclust 1.0.1 (2022-08-08)

• [GENERAL] A paper on the genieclust package has appeared in SoftwareX, see https://doi.org/10.1016/j.softx.2021.100722.

• [Python] 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.

Fixed build errors on Solaris: _X is a reserved identifier.

• Fixed missing LinkingTo: BH

• [Python] Python >= 3.7 is now required (implied by numpy).

• [R] Use RcppMLPACK directly instead of via a wrapper, emstreeR.