c_MeanShift: Mean Shift Clustering

In egenn/rtemis: Machine Learning and Visualization

Mean Shift Clustering

Description

Perform Mean Shift clustering using meanShiftR::meanShift

Usage

c_MeanShift(
  x,
  nNeighbors = NROW(x),
  algorithm = c("LINEAR", "KDTREE"),
  kernelType = c("NORMAL", "EPANECHNIKOV", "BIWEIGHT"),
  bandwidth = rep(1, NCOL(x)),
  alpha = 0,
  iterations = 10,
  epsilon = 1e-08,
  epsilonCluster = 1e-04,
  parameters = NULL,
  verbose = TRUE,
  ...
)

Arguments

x	Input matrix
nNeighbors	Integer: Number of neighbors to consider for kernel density estimate
algorithm	Character: "LINEAR" or "KDTREE"
kernelType	Character: "NORMAL", "EPANECHNIKOV", "BIWEIGHT"
bandwidth	Numeric vector, length = ncol(x): Use in kernel density estimation for steepest ascent classification.
alpha	Numeric: A scalar tuning parameter for normal kernels. When this parameter is set to zero, the mean shift algorithm will operate as usual. When this parameter is set to one, the mean shift algorithm will be approximated through Newton's Method. When set to a value between zero and one, a generalization of Newton's Method and mean shift will be used instead providing a means to balance convergence speed with stability.
iterations	Integer: Number of iterations to perform
epsilon	Numeric: used to determine when to terminate the iteration of an individual query point. If the distance between the query point at iteration i and i+1 is less than epsilon, then iteration ceases on this point.
epsilonCluster	Numeric: Used to determine the minimum distance between distinct clusters. This distance is applied after all iterations have finished and in order of the rows of queryData.
parameters	A scalar or vector of paramters used by the specific algorithm. There are no optional parameters for the "LINEAR" method, "KDTREE" supports optional parameters for the maximum number of points to store in a leaf node and the maximum value for the quadratic form in the normal kernel, ignoring the constant value -0.5.
verbose	Logical: If TRUE, print messages to console
...	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_NGAS(), c_PAM(), c_PAMK(), c_SPEC()

egenn/rtemis documentation built on Dec. 17, 2024, 6:16 p.m.