public void Test3()
{
var data = new List <float[]>();
data.Add(new float[] { 1.0f, 0.7f, 1.0f, });
data.Add(new float[] { -0.3f, -0.5f, -1.0f });
data.Add(new float[] { 3.0f, 0.1f, 1.0f });
data.Add(new float[] { -0.1f, -1.0f, -1.0f });
data.Add(new float[] { -1.0f, 1.1f, -1.0f });
data.Add(new float[] { 2.0f, -3.0f, 1.0f });
// ref probs, not working
var svm = new SVM();
for (int i = 0; i < 400; ++i)
{
var index = Random.Range(0, data.Count);
var x = new Unit(data[index][0], 0.0f);
var y = new Unit(data[index][1], 0.0f);
var label = data[index][2];
svm.LearnFrom(x, y, label);
if (i % 25 == 0)
{
Debug.LogFormat("training: {0}: accuracy: {1}", i, Evaluate(data, svm));
}
}
}
static void TraintSVM()
{
List <double[]> data = new List <double[]>();
List <int> labels = new List <int>();
data.Add(new[] { 1.2, 0.7 }); labels.Add(1);
data.Add(new[] { -0.3, -0.5 }); labels.Add(-1);
data.Add(new[] { 3.0, 0.1 }); labels.Add(1);
data.Add(new[] { -0.1, -1.0 }); labels.Add(-1);
data.Add(new[] { -1.0, 1.1 }); labels.Add(-1);
data.Add(new[] { 2.1, -3 }); labels.Add(1);
var svm = new SVM();
double initAcc = EvalTrainingAccuracy(data, labels, svm);
// the learning loop
for (var iter = 0; iter < 400; iter++)
{
// pick a random data point
int i = _rnd.Next(data.Count);
var x = new Unit(data[i][0], 0.0);
var y = new Unit(data[i][1], 0.0);
var label = labels[i];
svm.LearnFrom(x, y, label);
if (iter % 25 == 0)
{
double acc = EvalTrainingAccuracy(data, labels, svm);
Console.WriteLine("Training accuracy at iter " + iter + ": " + acc);
}
}
}
