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Setup CMeansConfig

Source: R/09_S7_ClusteringConfig.R
setup_CMeans.Rd

Setup CMeansConfig

Usage

setup_CMeans(
  k = 2L,
  max_iter = 100L,
  dist = c("euclidean", "manhattan"),
  method = c("cmeans", "ufcl"),
  m = 2,
  rate_par = NULL,
  weights = 1,
  control = list()
)

Arguments

k

Integer: Number of clusters.

max_iter

Integer: Maximum number of iterations.

dist

Character: Distance measure to use: 'euclidean' or 'manhattan'.

method

Character: "cmeans" - fuzzy c-means clustering; "ufcl": on-line update.

m

Float (>1): Degree of fuzzification.

rate_par

Float (0, 1): Learning rate for the online variant.

weights

Float (>0): Case weights.

control

List: Control config for clustering algorithm.

Value

CMeansConfig object.

Author

EDG

Examples

cmeans_config <- setup_CMeans(k = 4L, dist = "euclidean")
cmeans_config
#> <CMeans ClusteringConfig>
#>        k: <int> 4
#> max_iter: <int> 100
#>     dist: <chr> euclidean
#>   method: <chr> cmeans
#>        m: <nmr> 2.00
#> rate_par: <NUL> NULL
#>  weights: <nmr> 1.00
#>  control: (empty list)