ccacontrol: Utility function

In ConsRankClass: Classification and Clustering of Preference Rankings

Description

Utility function to use to set the control arguments of cca

Usage

ccacontrol(
  algorithm = "quick",
  full = FALSE,
  itercca = 1,
  consrankitermax = 10,
  np = 15,
  gl = 100,
  ff = 0.4,
  cr = 0.9,
  proc = FALSE,
  ps = FALSE
)

Arguments

algorithm	The algorithm used to compute the median ranking. One among"BB", "quick" (default), "fast" and "decor"
full	Specifies if the median ranking must be searched in the universe of rankings including all the possible ties. Default: FALSE
itercca	Number of iterations of cca
consrankitermax	Number of iterations for "fast" and "decor" algorithms. itermax=10 is the default option.
np	(for "decor" only) the number of population individuals. np=15 is the default option.
gl	(for"decor" only) generations limit, maximum number of consecutive generations without improvement. gl=100 is the default option.
ff	(for"decor" only) the scaling rate for mutation. Must be in [0,1]. ff=0.4 is the default option.
cr	(for"decor" only) the crossover range. Must be in [0,1]. cr=0.9 is the default option.
proc	(for "BB" only) proc=TRUE allows the branch and bound algorithm to work in difficult cases, i.e. when the number of objects is larger than 15 or 25. proc=FALSE is the default option
ps	If PS=TRUE, on the screen some information about how many branches are processed are displayed. Default value: FALSE

Value

A list containing all the control parameters

Author(s)

Antonio D'Ambrosio [e-mail]

See Also

cca

ConsRankClass documentation built on Sept. 28, 2021, 5:10 p.m.