Function kmedoids::pam[−][src]

pub fn pam<M, N>(
    mat: &M, 
    k: usize, 
    maxiter: usize
) -> (N, Vec<usize>, Vec<usize>, usize, usize) where
    N: NumAssignOps + Signed + Zero + PartialOrd + Copy + SafeAdd + Display,
    M: ArrayAdapter<N>, 

Implementation of the original PAM algorithm (BUILD + SWAP)

This is provided for academic reasons to see the performance difference. Quality-wise, FasterPAM is comparable to PAM, and much faster.

  • type M - matrix data type such as ndarray::Array2 or kmedoids::arrayadapter::LowerTriangle
  • type N - number data type such as i32 or f64 (must be signed)
  • mat - a pairwise distance matrix
  • k - the number of medoids to pick
  • maxiter - the maximum number of iterations allowed

returns a tuple containing:

  • the final loss
  • the final cluster assignment
  • the final medoids
  • the number of iterations needed
  • the number of swaps performed

Panics

  • panics when the dissimilarity matrix is not square
  • panics when k is 0 or larger than N

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 (loss, assi, meds, n_iter, n_swap) = kmedoids::pam(&data, 2, 100);
println!("Loss is: {}", loss);