fom: Figure of Merit

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

Description

The figure of merit evaluate the quality of a clustering algorithm by computing it on all features but one and then, it calculates the mean squared error on the remaining feature for each cluster. To find the optimal number of clusters, one has to find the "knee" in the curve.

Usage

fom(X, maxK, clusterAlg = myKmean, adjusted = TRUE, verbose = TRUE,
  ...)

Arguments

X	data matrix or data frame of size n x d, n observations and d features
maxK	maximum number of cluster to evaluate.
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.
adjusted	logical. If TRUE the adjusted figure of merit is returned.
verbose	logical. If true, the figure of merit is plotted against the nuber of clusters.
...	additional parameters for the clustering algorithm.

Value

fom_scores, the list of scores

References

Yeung, K. Y., Haynor, D. R., and Ruzzo, W. L. (2001). Validating clustering for gene expression data. Bioinformatics, 17(4):309-318. https://doi.org/10.1093/bioinformatics/17.4.309

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