ppam: Parallel Partitioning Around Medoids

Description Usage Arguments Details Author(s) See Also

View source: R/ppam.R

Description

Parallel implementation of the Partitioning Around Medoids algorithm, based on the cluster "pam" serial function.

Usage

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ppam(x, k, medoids = NULL, is_dist = inherits(x, "dist"), 
     cluster.only = FALSE, do.swap = TRUE, trace.lev = 0)

Arguments

x

input data, either a 2D array or an ff object

k

positive integer, indicating for the number of clusters

medoids

vector, with the initial 'k' medoids or NULL to let the algorithm select the initial medoids

is_dist

boolean, whether the input data is a distance or dissimilarity matrix or a symmetric matrix

cluster.only

boolean, whether only the clustering is computed and returned

do.swap

boolean, whether the swap phase of the algorithm is required

trace.lev

positive integer for the level of details returned for diagnostics

Details

The interface and parameters to parallel function ppam() are similar to the serial function pam() but not identical. ppam() requires a distance matrix as input parameters. Although, ppam() does not include the option to calculate the distance matrix, this can easily be done using SPRINT pcor() function with the 'distance' parameter set to TRUE.

N.B. Please see the SPRINT User Guide for how to run the code in parallel using the mpiexec command.

Author(s)

University of Edinburgh SPRINT Team [email protected] www.r-sprint.org

See Also

pam ff pcor SPRINT


sprint documentation built on May 30, 2017, 8:25 a.m.