void licz()
{
if (isAdaline)
learningMethod = new Model.Learning.Supervised.AdalineLMSLearningMethod();
else
learningMethod = new Model.Learning.Supervised.Bipolar.PerceptronLearningMethod();
learningMethod.Alpha = alpha;
learningMethod.Learn(net, learningSequence);
ble d = pop;
this.Invoke( d);
//pop();
}
static double testLearn(ISupervisedLearningMethod lm, LearningSequence<ISupervisedLearningVector> seq, ActivationFunction af, int no, double weight)
{
NeuralNetwork net;
double a = 0;
for (int i = 0; i < no; i++)
{
net = new NeuralNetwork();
net.Build(2, null, 1, af, weight);
lm.Learn(net, seq);
a += lm.LearningStory.Count;
}
return a / no;
}
