public async Task Classify()
{
var problemFactory = new ProblemFactory(threeClassDataset);
SvmTraining training = new SvmTraining(problemFactory, threeClassDataset);
var parameters = training.SelectParameters(TrainingHeader.CreateDefault(), CancellationToken.None);
var results = await training.Train(parameters).ConfigureAwait(false);
results.Model.Write(Path.Combine(TestContext.CurrentContext.TestDirectory, "classify.dat"));
var testSet = ArffDataSet.Create <PositivityType>("Test");
testSet.UseTotal = true;
var positive = testSet.AddDocument();
positive.AddRecord("Good");
var negative = testSet.AddDocument();
negative.AddRecord("Bad");
SvmTesting testing = new SvmTesting(results.Model, problemFactory);
testing.Classify(testSet);
Assert.AreEqual(PositivityType.Positive, positive.Class.Value);
Assert.AreEqual(PositivityType.Negative, negative.Class.Value);
}
public async Task TestTwoClass()
{
var problemFactory = new ProblemFactory(twoClassDataset);
SvmTraining training = new SvmTraining(problemFactory, twoClassDataset);
var parameters = training.SelectParameters(TrainingHeader.CreateDefault(), CancellationToken.None);
var results = await training.Train(parameters).ConfigureAwait(false);
var file = Path.Combine(TestContext.CurrentContext.TestDirectory, "data.arff");
threeClassDataset.Save(file);
var testFile = ArffDataSet.LoadSimple(file);
SvmTesting testing = new SvmTesting(results.Model, problemFactory);
var result = testing.Test(testFile, Path.Combine(TestContext.CurrentContext.TestDirectory, "."));
Assert.AreEqual(1, result);
}
public async Task TestMultiClass()
{
var dataSet = ArffDataSet.CreateSimple("Test");
dataSet.Header.RegisterNominalClass("One", "Two", "Three");
dataSet.UseTotal = true;
for (int i = 0; i < 20; i++)
{
var one = dataSet.AddDocument();
one.Class.Value = "One";
one.AddRecord("Good");
var two = dataSet.AddDocument();
two.Class.Value = "Two";
two.AddRecord("Bad");
var three = dataSet.AddDocument();
three.Class.Value = "Three";
three.AddRecord("Some");
}
var problemFactory = new ProblemFactory(dataSet);
SvmTraining training = new SvmTraining(problemFactory, dataSet);
var parameters = training.SelectParameters(TrainingHeader.CreateDefault(), CancellationToken.None);
var results = await training.Train(parameters).ConfigureAwait(false);
var file = Path.Combine(TestContext.CurrentContext.TestDirectory, "data.arff");
dataSet.Save(file);
results.Model.Write(Path.Combine(TestContext.CurrentContext.TestDirectory, "label.dat"));
var testFile = ArffDataSet.LoadSimple(file);
SvmTesting testing = new SvmTesting(results.Model, problemFactory);
var result = testing.Test(testFile, Path.Combine(TestContext.CurrentContext.TestDirectory, "."));
Assert.AreEqual(1, result);
}