Example #1
0
/*************************************************************************
Like MLPCreateR0, but for ensembles.

  -- ALGLIB --
	 Copyright 18.02.2009 by Bochkanov Sergey
*************************************************************************/
func MlpeCreateR0(nin, nout int, a, b float64, ensemblesize int, ensemble *mlpensemble) error {
	net := mlpbase.NewMlp()

	if err := mlpbase.MlpCreater0(nin, nout, a, b, net); err != nil {
		return err
	}
	return MlpeCreateFromNetwork(net, ensemblesize, ensemble)
}
Example #2
0
/*************************************************************************
Creates  neural  network  with  NIn  inputs,  NOut outputs, without hidden
layers with non-linear output layer. Network weights are filled with small
random values. Activation function of the output layer takes values [A,B].

  -- ALGLIB --
	 Copyright 30.03.2008 by Bochkanov Sergey
*************************************************************************/
func MlpCreateR0(nin, nout int, a, b float64) *MultiLayerPerceptron {
	network := NewMlp()
	mlpbase.MlpCreater0(nin, nout, a, b, network.innerobj)
	return network
}