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clValid (version 0.6-2)

clValid-class: Class "clValid"

Description

The class "clValid" contains the clustering results and validation measures from the accompanying call to the function clValid.

Arguments

Objects from the Class

Objects can be created using the function clValid.

References

Brock, G., Pihur, V., Datta, S. and Datta, S. (2008) clValid: An R Package for Cluster Validation Journal of Statistical Software 25(4) http://www.jstatsoft.org/v25/i04 Datta, S. and Datta, S. (2003) Comparisons and validation of statistical clustering techniques for microarray gene expression data. Bioinformatics 19(4): 459-466. Datta, S. and Datta, S. (2006) Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes. BMC Bioinformatics 7:397. http://www.biomedcentral.com/1471-2105/7/397 Handl, J., Knowles, K., and Kell, D. (2005) Computational cluster validation in post-genomic data analysis. Bioinformatics 21(15): 3201-3212.

See Also

For a description of the function 'clValid' see clValid. For help on the clustering methods see hclust and kmeans in package stats, kmeans in package stats, agnes, clara, diana, fanny, and pam in package cluster, som in package kohonen, Mclust in package mclust, and sota. For additional help on the validation measures see connectivity, dunn, stability, BHI, and BSI.

Examples

Run this code
## to delete
library(clValid)


data(mouse)

## internal validation
express <- mouse[1:25,c("M1","M2","M3","NC1","NC2","NC3")]
rownames(express) <- mouse$ID[1:25]
intern <- clValid(express, 2:6, clMethods=c("hierarchical","kmeans","pam"),
                  validation="internal")
slotNames(intern)

## view results
intern
summary(intern)
optimalScores(intern)
plot(intern)

## Extract objects from slots
measures(intern)
hierClust <- clusters(intern,"hierarchical")
plot(hierClust)
measNames(intern)
nClusters(intern)

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