Description Usage Arguments Details Value Note Author(s) References See Also Examples
View source: R/clValid-functions.R
Calculates the connectivity validation measure for a given cluster partitioning.
1 2 | connectivity(distance = NULL, clusters, Data = NULL, neighbSize = 10,
method = "euclidean")
|
distance |
The distance matrix (as a matrix object) of the
clustered observations. Required if |
clusters |
An integer vector indicating the cluster partitioning |
Data |
The data matrix of the clustered observations. Required if
|
neighbSize |
The size of the neighborhood |
method |
The metric used to determine the distance
matrix. Not used if |
The connectivity indicates the degree of connectedness of the
clusters, as determined by the k-nearest neighbors. The
neighbSize
argument specifies the number of neighbors to use.
The connectivity has a value between 0 and infinity and should be minimized.
For details see the package vignette.
Returns the connectivity measure as a numeric value.
The main function for cluster validation is clValid
, and
users should call this function directly if possible.
Guy Brock, Vasyl Pihur, Susmita Datta, Somnath Datta
Handl, J., Knowles, K., and Kell, D. (2005). Computational cluster validation in post-genomic data analysis. Bioinformatics 21(15): 3201-3212.
For a description of the function 'clValid' see clValid
.
For a description of the class 'clValid' and all available methods see
clValidObj
or clValid-class
.
For additional help on the other validation measures see
dunn
,
stability
,
BHI
, and
BSI
.
1 2 3 4 5 6 7 8 9 | data(mouse)
express <- mouse[1:25,c("M1","M2","M3","NC1","NC2","NC3")]
rownames(express) <- mouse$ID[1:25]
## hierarchical clustering
Dist <- dist(express,method="euclidean")
clusterObj <- hclust(Dist, method="average")
nc <- 2 ## number of clusters
cluster <- cutree(clusterObj,nc)
connectivity(Dist, cluster)
|
Loading required package: cluster
[1] 4.615873
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