public void CanReadTabSeparatedList() { var reader = new TabSeparatedListReader(); List <KeyValuePair <double, double[]> > set = reader.Read(@"..\..\trainingsets\dataset2\biased.txt"); Assert.AreEqual(208, set.Count); }
public void FTClassifiesBiasedData() { // data has 2 double inputs and an expected binary out var network = new PerceptronFactory().BuildFTPerceptron(2); var reader = new TabSeparatedListReader(); List <KeyValuePair <double, double[]> > trainingSet = reader.Read(@"..\..\trainingsets\dataset2\biased.txt"); network.Train(trainingSet); trainingSet.ForEach(kvp => Assert.AreEqual(kvp.Key, network.Classify(kvp.Value))); }
public void CanReadTabSeparatedList() { var reader = new TabSeparatedListReader(); List<KeyValuePair<double, double[]>> set = reader.Read(@"..\..\trainingsets\dataset2\biased.txt"); Assert.AreEqual(208, set.Count); }
public void FTClassifiesBiasedData() { // data has 2 double inputs and an expected binary out var network = new PerceptronFactory().BuildFTPerceptron(2); var reader = new TabSeparatedListReader(); List<KeyValuePair<double, double[]>> trainingSet = reader.Read(@"..\..\trainingsets\dataset2\biased.txt"); network.Train(trainingSet); trainingSet.ForEach(kvp => Assert.AreEqual(kvp.Key, network.Classify(kvp.Value))); }