This tutorial covers how to apply RBF (Radial Basis Function Network) to find best fit and to forecast next data values.

  1. Select data series 'Raw data' on left panel [Points].
  2. To add rectangle area, select menu item <Edit><Areas><Rectangle Area>, and draw area with mouse.
  3. To select area, select menu item <Edit><Select Area>, and click left on rectangle.
  4. Click right and in popup menu select item menu item <Transform red selected points>.
  5. Click button Apply RBFN.
  6. In dialog select History points M = 8
  7. Method uses X[i] and M history data values Y[i-M+1],...Y[i] to fit Y[i+1].
  8. Select 4 neurons on hidden layer.
  9. Select checked both 'Normalized' and 'Local linear model'.
  10. Select Gaussian activation function.
  11. Select 10 data points to forecast.
  12. Click Forecast.
  13. Close the dialog.