calcSFCMBelongMatrixNoisy: Calculate the membership matrix (spatial version) with a...
In geocmeans: Implementing Methods for Spatial Fuzzy Unsupervised Classification

calcSFCMBelongMatrixNoisy

R 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