Encog.Neural.Networks.BasicNetwork.Classify C# (CSharp) Метод

        public int Classify(IMLData input)
        {
            return Winner(input);
        }

        public void Train()
        {
            TrainingErrorData.Clear();
            TestingIdealData.Clear();
            TestingResultsData.Clear();
            _network = ConstructNetwork(TrainingSet.InputSize,TrainingSet.IdealSize);

            //var trainer = new Backpropagation(_network, TrainingSet, LearningRate, Momentum);
            var trainer = new ResilientPropagation(_network, TrainingSet);
            double[] resultsArray = new double[TrainingSet.Count];
            double[] errorArray = new double[NumberOfIterations];
            IsBusy = true;
            for (int iteration = 0; iteration < numberOfIterations; iteration++)
            {
                trainer.Iteration();
                TrainingErrorData.Add(new Tuple<int,double>(iteration, trainer.Error));
            }
            IsBusy = false;
            for(int i = 0; i < TrainingSet.Count; i++)
            {
               resultsArray[i] = _network.Classify(TrainingSet[i].Input);
            }
            TrainingErrorValue = _network.CalculateError(TrainingSet);
            Stage = Stage.Trained;
        }