functionality of this program :

• Single-Layer Radial Basis Function (RBF) Architecture Implementation

  X contains inputs
  X =[ (X¹)   ...  (X^L)]
  G is matrix which contains g_i(X^j) (which are outputs of each RBF node)
  g_i = e ^{(-‫γ‬_i (X - V_i)^T(X-V_i))}       ‫γ_i‬ is i^th constant and V_i is i^th center
  G = [ g₁(X¹)   ...   g_m(X¹)
          .
          .
          .
          g₁(X^L) ... g_m(X^L) ]
  W is a vector contains weights between RBF layer and output
  W =[ (w₁)
          .
          .
          .
          (w_m) ]
  ‫̂y‬= GW
  

• Single-Layer RBF weights calculation

  W = (G^T G)^-1 G^T y

• Single-Layer RBF error calculation

  L is our loss function (to calculate error)
  ‫‪L(ŷ,y) = 1/2 - (ŷ - y)^T(ŷ - y)

• Evolution Strategy algorithm with V(vector) and ‫‫‫‫‫‫‫γ(scalar) parameters

  • ES(MU, LAMBDA)
  • Mutation strategy needs to be more precise
  • alternative chromosome length

• Reach High accuracy for regression
  

  • Show Results with current Architecture for Regression Problem
    

  

• Reach High accuracy for two class
  

  • Show Results with current Architecture for Classification Problem

• Reach High accuracy for (multi class) classification
  

  • loss function need to be more accurate