Learning fuzzy models

FuzzyLogic.fuzzy_cmeans — Function
fuzzy_cmeans(
    X::Array{T<:Real, 2},
    N::Int64;
    m,
    maxiter,
    tol
) -> Tuple{Any, Any}

Performs fuzzy clustering on th data X using N clusters.

Input

  • X – $d × M$ matrix of data, each column is a data point
  • N – number of clusters used.

Keyword argumes

  • m – exponent of the fuzzy membership function, default 2.0
  • maxiter – maximum number of iterations, default 100
  • tol – absolute error for stopping condition. Stop if $|Eₖ - Eₖ₊₁|≤tol$, where $Eₖ$ is the cost function value at the $k$:th iteration.

Output

  • C – $d × N$matrix of centers, each column is the center of a cluster.
  • U – $M × N$ matrix of membership degrees, Uᵢⱼtells has the membership degree of thejth point to thei`th cluster.