Lib.rs

› Algorithms
#clustering #cluster #data-science

cogset

Generic implementations of clustering algorithms. Includes k-means, DBSCAN and OPTICS.

by Huon Wilson

3 unstable releases

Uses old Rust 2015

0.2.0 Apr 29, 2015
0.1.1 Apr 27, 2015
0.1.0 Apr 10, 2015

#2197 in Algorithms

Download history 334/week @ 2024-07-26 318/week @ 2024-08-02 261/week @ 2024-08-09 360/week @ 2024-08-16 338/week @ 2024-08-23 196/week @ 2024-08-30 280/week @ 2024-09-06 153/week @ 2024-09-13 323/week @ 2024-09-20 167/week @ 2024-09-27 181/week @ 2024-10-04 246/week @ 2024-10-11 303/week @ 2024-10-18 154/week @ 2024-10-25 169/week @ 2024-11-01 191/week @ 2024-11-08

885 downloads per month

MIT/Apache

40KB
734 lines

cogset

Build Status

A cluster

Generic implementations of clustering algorithms.

Documentation, crates.io.

lib.rs:

Clustering algorithms.

A cluster

This crate provides generic implementations of clustering algorithms, allowing them to work with any back-end "point database" that implements the required operations, e.g. one might be happy with using the naive collection BruteScan from this crate, or go all out and implement a specialised R*-tree for optimised performance.

Density-based clustering algorithms:

  • DBSCAN (Dbscan)
  • OPTICS (Optics)

Others:

  • k-means (Kmeans)

Source.

Installation

Add the following to your Cargo.toml file:

[dependencies]
cogset = "0.1"

Dependencies

~20KB