- data
frame or matrix containing the data. Rows correspond to observations
and columns correspond to variables.
- nbCluster
[vector
] listing the number of clusters to test.
- dim
integer giving the dimension of the Gaussian density. Default is 10.
- models
[vector
] of model names to run. By default only
"kmm_pk_s" is estimated. All the model names are given by the method
[kmmNames
].
- kernelName
string with a kernel name. Possible values:
"Gaussian", "polynomial", "Laplace", "linear", "rationalQuadratic_", "Hamming".
Default is "Gaussian".
- kernelParameters
[vector
] with the parameters of
the chosen kernel. Default is c(1).
- kernelComputation
[logical
] parameter. Should be TRUE
if the Gram matrix is to be computed (faster but can be memory consuming), FALSE
otherwise (times consuming). Default is TRUE
. Recall that Gram matrix
is a square matrix of size nbSample.
- strategy
a [ClusterStrategy
] object containing
the strategy to run. [kmmStrategy
]() method by default.
- criterion
character defining the criterion to select the best model.
The best model is the one with the lowest criterion value.
Possible values: "BIC", "AIC", "ICL", "ML". Default is "ICL".
- nbCore
integer defining the number of processor to use (default is 1, 0 for all).