dbscan

A fast reimplementation of several density-based algorithms of the DBSCAN family. Includes the clustering algorithms DBSCAN (density-based spatial clustering of applications with noise) and HDBSCAN (hierarchical DBSCAN), the ordering algorithm OPTICS (ordering points to identify the clustering structure), shared nearest neighbor clustering, and the outlier detection algorithms LOF (local outlier factor) and GLOSH (global-local outlier score from hierarchies). The implementations use the kd-tree data structure (from library ANN) for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided. Hahsler, Piekenbrock and Doran (2019) doi:10.18637/jss.v091.i01.

Last 30 days

This package has been downloaded 33,538 times in the last 30 days. The downloads are officially high enough to crash an underfunded departmental server. Quite an accomplishment! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 1,232 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 384,802 times in the last 365 days. That's a whole lot of downloads. Somewhere, a librarian is trying to figure out why more bandwidth is needed. The day with the most downloads was Dec 14, 2024 with 9,817 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.