center

Where, is the number of outputs () and is the number of inputs

Key Model Selection Decisions:

  1. Number of RBF units (hidden neurons) - How many radial basis functions to use in the hidden layer
  2. RBF centers - Where to position each RBF unit in the input space (the centers of the Gaussian functions)
  3. RBF widths (σ or spread parameters) - The width/spread of each radial basis function, which controls how much of the input space each unit responds to
  4. Output weights () - The weights connecting the RBF units to the output layer