c_SPEC: Spectral Clustering

In egenn/rtemis: Machine Learning and Visualization

Spectral Clustering

Description

Perform Spectral Clustering using kernlab::specc

Usage

c_SPEC(
  x,
  k = 2,
  kernel = "rbfdot",
  kpar = "automatic",
  nystrom.red = FALSE,
  nystrom.sample = dim(x)[1]/6,
  iterations = 200,
  mod.sample = 0.75,
  na.action = na.omit,
  verbose = TRUE,
  ...
)

Arguments

x	Input matrix / data.frame
k	Integer: Number of clusters to get
kernel	Character: Kernel to use: "rbfdot", "polydot", "vanilladot", tanhdot", "laplacedot", "besseldot", "anovadot", "splinedot", "stringdot"
kpar	String OR List: "automatic", "local" OR list with: sigma (for "rbfdor", "laplacedot"); degree, scale, offset (for "polydot"); scale, offset (for "tanhdot"); sigma, order, degree (for "besseldot"); sigma, degree (for "anovadot"); length, lambda, normalized (for "stringdot")
nystrom.red	Logical: if TRUE, use nystrom method to calculate eigenvectors (Default = FALSE)
nystrom.sample	Integer: Number of points to use for estimating the eigenvalues when nystrom.red = TRUE Default = dim(x)[1]/6
iterations	Integer: Number of iterations allowed
mod.sample	Float (0, 1): Proportion of data to use when estimating sigma. Default = .75
na.action	Function: Action to perform on NA (Default = na.omit)
verbose	Logical: If TRUE, print messages to screen
...	Additional parameters to be passed to flexclust::cclust

Author(s)

E.D. Gennatas

See Also

Other Clustering: c_CMeans(), c_DBSCAN(), c_EMC(), c_H2OKMeans(), c_HARDCL(), c_HOPACH(), c_KMeans(), c_MeanShift(), c_NGAS(), c_PAM(), c_PAMK()

egenn/rtemis documentation built on May 4, 2024, 7:40 p.m.