calcSFGCMBelongMatrixNoisy: Calculate the generalized membership matrix (spatial version)...

In JeremyGelb/geocmeans: Implementing Methods for Spatial Fuzzy Unsupervised Classification

Calculate the generalized membership matrix (spatial version) with a noise cluster

Description

Calculate the generalized membership matrix (spatial version) with a noise cluster

Usage

calcSFGCMBelongMatrixNoisy(
  centers,
  data,
  wdata,
  m,
  alpha,
  beta,
  delta,
  sigmas,
  wsigmas
)

Arguments

centers	A matrix representing the centers of the clusters with p columns and k rows
data	A matrix representing the observed data with n rows and p columns
wdata	A matrix representing the lagged observed data with n rows and p columns
m	A float representing the fuzziness degree
alpha	A float representing the weight of the space in the analysis (0 is a typical fuzzy-c-mean algorithm, 1 is balanced between the two dimensions, 2 is twice the weight for space)
beta	A float for the beta parameter (control speed convergence and classification crispness)
delta	A float, the value set for delta by the user
sigmas	A numeric vector for calculating the robust version of the FCM. Filled with ones if the classical version is required
wsigmas	Same as sigmas, but calculated on the spatially lagged dataset

Value

A n * k matrix representing the belonging probabilities of each observation to each cluster

JeremyGelb/geocmeans documentation built on Nov. 20, 2024, 2:50 p.m.