public void DeltaRuleLearning_Test_iterations_1000_learningrate_02() { loadRealDataSample(); // System coefficients initialization. var desc = loadMetaData(); // Description of the system. LearningApi api = new LearningApi(desc); //Real dataset must be defined as object type, because data can be numeric, binary and classification api.UseActionModule <double[, ], double[, ]>((input, ctx) => { return(loadRealDataSample()); // return actual System coefficients data }); // run input = UseActionModule output //run Delta Rule for 1000 iterations with learningRate=0.2 api.UseDeltaRuleLearning(0.2, 1000); var result = api.Run() as double[]; Debug.WriteLine("************ Output Predictions***********"); for (int i = 0; i < result.Length; i++) { if (result[i] != 0) { Debug.WriteLine(result[i]); } } using (var fs = File.OpenRead(@"H_Test.csv")) using (var reader = new StreamReader(fs)) { while (!reader.EndOfStream) { var line = reader.ReadLine(); var values = line.Split(','); ti = new double[values.Length]; to = new double[values.Length]; for (int i = 0; i < values.Length; i++) { var val = values[i].Split(' '); double.TryParse(val[0], out x); double.TryParse(val[1], out y); ti[i] = x; to[i] = y; } } } for (int i = 0; i < to.Length; i++) { //Testing of Test data with Predicted System model Assert.Equal(Math.Round(result[i], 4), Math.Round(to[i], 4)); } }