evalCluster {flowPeaks} | R Documentation |
This function takes the cluster labels of the two clusterings, one is based on the gold standard, the other is a candidate clusterign, and compute one of the three metrics to assess the candidate clustering performance.
evalCluster(gs,cand,method=c("Rand.index","Fmeasure","Vmeasure"), rm.gs.outliers=TRUE)
gs |
A integer-valued vector of length n for the cluster labels of the gold standard clustering, where negative numbers such as -1 is for the outerliers |
cand |
A integer-valued vector of length n for the cluster label of a candidate clustering, where -1 is for the outliers |
rm.gs.outliers |
Determining whether the outliers of the gold standard clustering should be removed in the comparison |
method |
A single character to indicate which one of three metrics
should be used to evaluate the clustering. The details are described in
Ge (2012) and references mentioned in that paper
|
Yongchao Ge yongchao.ge@gmail.com
Ge Y. et al, flowPeaks: a fast unsupervised clustering for flow cytometry data via K-means and density peak finding, 2012, Bioinformatics 8(15):2052-8