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; }