Clustering : Parameters used in clustering

# clusterAxis
Axis to use when clustering data
Type: string
Default: samples
Options: samples, variables

# clusteringDistance
Distance metric to use when clustering data
Type: string
Default: euclidianDistance
Options: euclidianDistance, manhattanDistance, maxDistance

clusteringDistance : "euclidianDistance"

clusteringDistance : "manhattanDistance"

clusteringDistance : "maxDistance"


# imputeMethod
Imputation method for missing data when clustering
Type: string
Default: mean
Options: mean, median

# kmeansSmpClusters
Number of clusters when clustering sample data with kmeans
Type: integer
Default: 3

kmeansSmpClusters : 2

kmeansSmpClusters : 3

kmeansSmpClusters : 4


# kmeansVarClusters
Number of clusters when clustering variable data with kmeans
Type: integer
Default: 3

kmeansVarClusters : 2

kmeansVarClusters : 3

kmeansVarClusters : 4


# linkage
Linkage type to use when clustering data
Type: string
Default: complete
Options: single, complete, average

linkage : "single"

linkage : "complete"

linkage : "average"


# maxIterations
Number of maximum iterations when clustering data with kmeans for one dimensional graphs or maximum number of iterations when calculating force direct layout networks
Type: integer
Default: 500

# samplesClustered
Flag to cluster samples
Type: boolean
Default: false

samplesClustered : true

samplesClustered : false


# samplesKmeaned
Flag to k-mean samples
Type: boolean
Default: false

samplesKmeaned : true

samplesKmeaned : false


# variablesClustered
Flag to cluster variables
Type: boolean
Default: false

variablesClustered : true

variablesClustered : false


# variablesKmeaned
Flag to k-mean variables
Type: boolean
Default: false

variablesKmeaned : true

variablesKmeaned : false