eval_parameters: Worker function

In geocmeans: Implementing Methods for Spatial Fuzzy Unsupervised Classification

Worker function

Description

Worker function for select_parameters and select_parameters.mc

Usage

eval_parameters(
  algo,
  parameters,
  data,
  nblistw = NULL,
  window = NULL,
  standardize = TRUE,
  robust = FALSE,
  noise_cluster = FALSE,
  spconsist = FALSE,
  classidx = TRUE,
  nrep = 30,
  indices = NULL,
  tol,
  maxiter,
  seed = NULL,
  init = "random",
  verbose = TRUE,
  wrapped = FALSE
)

Arguments

algo	A string indicating which method to use (FCM, GFCM, SFCM, SGFCM)
parameters	A dataframe of parameters with columns k,m and alpha
data	A dataframe with numeric columns
nblistw	A list.w object describing the neighbours typically produced by the spdep package. Required if data is a dataframe, see the parameter window if you use a list of rasters as input.
window	If data is a list of rasters, then a window must be specified instead of a list.w object. It will be used to calculate a focal function on each raster. The window must be a square numeric matrix with odd dimensions (such 3x3). The values in the matrix indicate the weight to give to each pixel and the centre of the matrix is the centre of the focal function.
standardize	A boolean to specify if the variable must be centered and reduce (default = True)
spconsist	A boolean indicating if the spatial consistency must be calculated
classidx	A boolean indicating if the quality of classification indices must be calculated
nrep	An integer indicating the number of permutation to do to simulate the random distribution of the spatial inconsistency. Only used if spconsist is TRUE.
indices	A character vector with the names of the indices to calculate, to evaluate clustering quality. default is :c("Silhouette.index", "Partition.entropy", "Partition.coeff", "XieBeni.index", "FukuyamaSugeno.index", "Explained.inertia"). Other available indices are : "DaviesBoulin.index", "CalinskiHarabasz.index", "GD43.index", "GD53.index" and "Negentropy.index".
tol	The tolerance criterion used in the evaluateMatrices function for convergence assessment
maxiter	An integer for the maximum number of iteration
seed	An integer used for random number generation. It ensures that the start centers will be the same if the same integer is selected.
init	A string indicating how the initial centers must be selected. "random" indicates that random observations are used as centers. "kpp" use a distance based method resulting in more dispersed centers at the beginning. Both of them are heuristic.
verbose	A boolean indicating if a progressbar should be displayed
wrapped	A boolean indicating if the data passed is wrapped or not (see wrap function of terra)

Value

a DataFrame containing for each combinations of parameters several clustering quality indexes.

Examples

#No example provided, this is an internal function

geocmeans documentation built on Sept. 12, 2023, 9:06 a.m.