public Test(ReseauNeurone neuronet, MnistDatabase baseTest, FormPrincipal frm)
{
_RNN = neuronet;
BaseApprentissage = baseTest;
nombre = BaseApprentissage.imageCount;
erreurReconnaissances = 0;
_form = frm;
m_HiPerfTime = new HiPerfTimer();
}
public Test(ReseauNeurone neuronet, MnistDatabase baseTest, FormPrincipal frm, int entree, int sortie, int taille)
{
_RNN = neuronet;
BaseApprentissage = baseTest;
nombre = BaseApprentissage.imageCount;
erreurReconnaissances = 0;
_form = frm;
m_HiPerfTime = new HiPerfTimer();
this.Entree = entree;
this.Sortie = sortie;
this.Taille = taille;
}
public Apprentissage(ReseauNeurone neuronet, MnistDatabase baseApprentissage, int nombreSorties, FormPrincipal frm, Boolean distorsion)
{
_RNN = neuronet;
BaseApprentissage = baseApprentissage;
nombre = baseApprentissage.imageCount;
NombreSorties = nombreSorties;
erreurReconnaissances = 0;
bonneReconnaissances = 0;
nombreBackPropagation = 0;
_iEpochsCompleted = 0;
_form = frm;
m_HiPerfTime = new HiPerfTimer();
archive = new Archive();
this.Distorsion = distorsion;
}
public Apprentissage(ReseauNeurone neuronet, double[][] trainMatrix, int nombreSorties, FormPrincipal frm, Boolean distorsion)
{
_RNN = neuronet;
TrainMatrix = trainMatrix;
SizePattern = Convert.ToInt32(Math.Sqrt(TrainMatrix[0].Length));
// nombre = baseApprentissage.imageCount;
NombreSorties = nombreSorties;
erreurReconnaissances = 0;
bonneReconnaissances = 0;
nombreBackPropagation = 0;
_iEpochsCompleted = 0;
_form = frm;
m_HiPerfTime = new HiPerfTimer();
archive = new Archive();
this.Distorsion = distorsion;
}
