BSD Ports

math/py-hdbscan 0.8.33_1 DragonFly

Clustering based on density with variable density clusters

System
DragonFly
Repository
DPorts
Maintainer
[email protected] (as in FreeBSD)
License
BSD3CLAUSE
Categories
math, python
Package size
450.4 KiB, 2198.2 KiB installed

Description

HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates the result to find a clustering that gives the best stability over epsilon. This allows HDBSCAN to find clusters of varying densities (unlike DBSCAN), and be more robust to parameter selection.

In practice this means that HDBSCAN returns a good clustering straight away with little or no parameter tuning -- and the primary parameter, minimum cluster size, is intuitive and easy to select.

HDBSCAN is ideal for exploratory data analysis; it's a fast and robust algorithm that you can trust to return meaningful clusters (if there are any).

In the other systems

SystemPortVersion
DragonFlymath/py-hdbscan0.8.33_1
FreeBSDmath/py-hdbscan0.8.44

Install

Binary package:

pkg install py311-hdbscan

From DPorts:

cd /usr/dports/math/py-hdbscan && make install clean

Dependencies

Run dependencies 5

No port depends on this one.