ModelExplorer: Stability measure for finding the number of clusters

In mattmail/clusterAnalysis: Several tools for determining the number of clusters in a dataset

Description

Model Explorer measures the stability of a given clustering method on subsambles of the original dataset. It plots the cumulative distribution of the stability measure. The more the distribution is concentrated on the right, the better.

Usage

ModelExplorer(X, maxK, similarity = adj.rand.index,
  clusterAlg = myKmean, rho = 0.8, B = 100, verbose = FALSE, ...)

Arguments

X	data matrix or data frame of size n x d, n observations and d features
maxK	maximum number of clusters to evaluate.
similarity	function measuring the similarity between two partitions.
clusterAlg	clustering algorithm. Its output must be a list having a compoment "cluster" containing the assignation of each observation. For more details, check the formatting of function myKmean.
rho	numeric between 0 and 1. Proportional size of the subsamples.
B	Number of resampling iterations.
verbose	logical. If TRUE, it plot the evolution of the algorithm.
...	additional parameters for the clustering algorithm.

Value

Matrix of size maxK-1 x B containing the stability measure for each iteration.

References

Ben-Hur, A., Elisseeff, A., and Guyon, I. (2002). A stability based method for discovering structure in clustered data.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2002:6-17

mattmail/clusterAnalysis documentation built on Nov. 4, 2019, 6:18 p.m.