예제 #1
0
파일: mlpe.go 프로젝트: rutmir/pr.optima
/*************************************************************************
Like MLPCreateC0, but for ensembles.

  -- ALGLIB --
	 Copyright 18.02.2009 by Bochkanov Sergey
*************************************************************************/
func MlpeCreateC0(nin, nout, ensemblesize int, ensemble *mlpensemble) error {
	net := mlpbase.NewMlp()

	if err := mlpbase.MlpCreatec0(nin, nout, net); err != nil {
		return err
	}
	return MlpeCreateFromNetwork(net, ensemblesize, ensemble)
}
예제 #2
0
파일: neural.go 프로젝트: rutmir/pr.optima
/*************************************************************************
Creates classifier network with NIn  inputs  and  NOut  possible  classes.
Network contains no hidden layers and linear output  layer  with  SOFTMAX-
normalization  (so  outputs  sums  up  to  1.0  and  converge to posterior
probabilities).

  -- ALGLIB --
	 Copyright 04.11.2007 by Bochkanov Sergey
*************************************************************************/
func MlpCreateC0(nin, nout int) *MultiLayerPerceptron {
	network := NewMlp()
	mlpbase.MlpCreatec0(nin, nout, network.innerobj)
	return network
}