genieclust

A retake on the Genie algorithm (Gagolewski, 2021 doi:10.1016/j.softx.2021.100722) - a robust hierarchical clustering method (Gagolewski, Bartoszuk, Cena, 2016 doi:10.1016/j.ins.2016.05.003). Now faster and more memory efficient; determining the whole hierarchy for datasets of 10M points in low dimensional Euclidean spaces or 100K points in high-dimensional ones takes only 1-2 minutes. Allows clustering with respect to mutual reachability distances so that it can act as a noise point detector or a robustified version of 'HDBSCAN*' (that is able to detect a predefined number of clusters and hence it does not dependent on the somewhat fragile 'eps' parameter). The package also features an implementation of inequality indices (the Gini, Bonferroni index), external cluster validity measures (e.g., the normalised clustering accuracy and partition similarity scores such as the adjusted Rand, Fowlkes-Mallows, adjusted mutual information, and the pair sets index), and internal cluster validity indices (e.g., the Calinski-Harabasz, Davies-Bouldin, Ball-Hall, Silhouette, and generalised Dunn indices). See also the 'Python' version of 'genieclust' available on 'PyPI', which supports sparse data, more metrics, and even larger datasets.

Last 30 days

This package has been downloaded 570 times in the last 30 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 43 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 8,162 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was Aug 22, 2024 with 128 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.