calcSFCMBelongMatrixNoisy: Calculate the membership matrix (spatial version) with a...

View source: R/RcppExports.R

calcSFCMBelongMatrixNoisyR Documentation

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

Description

Calculate the membership matrix (spatial version) according to a set of centroids, the observed data, the fuzziness degree a neighbouring matrix and a spatial weighting term

Usage

calcSFCMBelongMatrixNoisy(
  centers,
  data,
  wdata,
  m,
  alpha,
  delta,
  sigmas,
  wsigmas
)

Arguments

centers

A matrix or a dataframe 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)

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


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