public void TrainTest1()
{
const int LearnCount = 100;
const int TestCount = 1000;
const int Length = 300;
const double PositiveRatio = 0.1;
// create samples
List <(float[] x, bool y, float weight)> samples = SupportVectorMachineTest.GenerateSamples(LearnCount + TestCount, Length, PositiveRatio)
.Select(x => (x.x.Select(w => (float)w).ToArray(), x.y, (float)x.weight))
.ToList();
// learn
SequentualMinimalOptimization smo = new SequentualMinimalOptimization(new ChiSquare())
{
Algorithm = SMOAlgorithm.LibSVM,
Tolerance = 0.01f,
};
SupportVectorMachine machine = SupportVectorMachine.Learn(
smo,
samples.Take(LearnCount).Select(x => x.x).ToList(),
samples.Take(LearnCount).Select(x => x.y).ToList(),
samples.Take(LearnCount).Select(x => x.weight).ToList(),
CancellationToken.None);
// test
List <ClassificationResult <bool?> > results = samples
.Skip(LearnCount)
.Select(x => new ClassificationResult <bool?>(null, machine.Classify(x.x) > 0.5f, x.y, 1.0f, true))
.ToList();
ClassificationReport <bool?> report = new ClassificationReport <bool?>(results);
}
