Crate kmedoids

k-Medoids Clustering with the FasterPAM Algorithm

For details on the implemented FasterPAM algorithm, please see:

Erich Schubert, Peter J. Rousseeuw
Fast and Eager k-Medoids Clustering:
O(k) Runtime Improvement of the PAM, CLARA, and CLARANS Algorithms
Under review at Information Systems, Elsevier.
Preprint: https://arxiv.org/abs/2008.05171

Erich Schubert, Peter J. Rousseeuw:
Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms
In: 12th International Conference on Similarity Search and Applications (SISAP 2019), 171-187.
https://doi.org/10.1007/978-3-030-32047-8_16
Preprint: https://arxiv.org/abs/1810.05691

This is a port of the original Java code from ELKI to Rust. But it does not include all functionality in the original benchmarks.

If you use this in scientific work, please consider citing above articles.

Example

Given a dissimilarity matrix of size 4 x 4, use:

let data = ndarray::arr2(&[[0,1,2,3],[1,0,4,5],[2,4,0,6],[3,5,6,0]]);
let mut meds = kmedoids::random_initialization(4, 2, &mut rand::thread_rng());
let (loss, assi, n_iter, n_swap) = kmedoids::fasterpam(&data, &mut meds, 100);
println!("Loss is: {}", loss);

Re-exports

pub use crate::arrayadapter::ArrayAdapter;

pub use crate::safeadd::SafeAdd;

Modules

arrayadapter	Adapter trait for accessing different types of arrays.
safeadd	Add without overflow, for both integer and float types.

Functions

fasterpam	Run the FasterPAM algorithm.
fastpam1	Run the FastPAM1 algorithm, which yields the same results as the original PAM.
pam	Implementation of the original PAM algorithm (BUILD + SWAP)
pam_build	Implementation of the original PAM BUILD algorithm.
pam_swap	Implementation of the original PAM SWAP algorithm (no BUILD).
random_initialization	Random initialization (requires the rand crate)