public void SquaredHinge()
{
double actual;
actual = new SquaredHingeLoss(new[] { 0, 1, -0.5, 0.8 }).Loss(new[] { 0, 1, -0.5, 0.8 });
Assert.AreEqual(0.645, actual);
actual = new SquaredHingeLoss(new[] { 0, 1, -0.5, 0.8 }).Loss(new[] { 0, 1, 0.5, 0.8 });
Assert.AreEqual(1.645, actual);
actual = new SquaredHingeLoss(new[] { 0, 1, -0.5, 0.8 }).Loss(new[] { -5, 1, 0.5, 0.8 });
Assert.AreEqual(1.145, actual);
actual = new SquaredHingeLoss(new[] { 5.4, 1, -0.5, 0.8 }).Loss(new[] { -5.2, 1, 0.5, 0.8 });
Assert.AreEqual(20.365, actual, 1e-10);
actual = new SquaredHingeLoss(new int[] { 0, 1, 0, 0 }).Loss(new double[] { 1, 1, 1, 1 });
Assert.AreEqual(2, actual);
actual = new SquaredHingeLoss(new int[] { 0, 1, 0, 0 }).Loss(new double[] { 0, 0, 0, 0 });
Assert.AreEqual(2, actual);
actual = new SquaredHingeLoss(new int[] { -1, 1, -1, -1 }).Loss(new double[] { -1, -1, -1, -1 });
Assert.AreEqual(6, actual);
actual = new SquaredHingeLoss(new int[] { 0, 0, 0, 1 }).Loss(new double[] { -1, 1, 1, 1 });
Assert.AreEqual(4, actual);
actual = new SquaredHingeLoss(new int[] { 0, 0, 0, 1 }).Loss(new double[] { -1, -1, -1, 1 });
Assert.AreEqual(8, actual);
actual = new SquaredHingeLoss(new int[] { -1, -1, -1, 1 }).Loss(new double[] { 0, 0, 0, 1 });
Assert.AreEqual(3.5, actual);
actual = new SquaredHingeLoss(new double[] { 0, 1, 0, 0 }).Loss(new double[] { 0, 0, 0, 0 });
Assert.AreEqual(2, actual);
Assert.AreEqual(0, new SquaredHingeLoss().Loss(1, 1));
Assert.AreEqual(2, new SquaredHingeLoss().Loss(-1, 1));
Assert.AreEqual(2, new SquaredHingeLoss().Loss(1, -1));
Assert.AreEqual(0, new SquaredHingeLoss().Loss(-1, -1));
Assert.AreEqual(0, new SquaredHingeLoss().Loss(1, 5));
Assert.AreEqual(24.5, new SquaredHingeLoss().Loss(-1, 6));
Assert.AreEqual(32, new SquaredHingeLoss().Loss(1, -7));
Assert.AreEqual(0, new SquaredHingeLoss().Loss(-1, -8));
Assert.AreEqual(2, new SquaredHingeLoss().Loss(-1, 1));
Assert.AreEqual(0.5, new SquaredHingeLoss().Loss(1, 0));
Assert.AreEqual(0.5, new SquaredHingeLoss().Loss(-1, 0));
Assert.AreEqual(0, new SquaredHingeLoss().Loss(true, 5));
Assert.AreEqual(24.5, new SquaredHingeLoss().Loss(false, 6));
Assert.AreEqual(32, new SquaredHingeLoss().Loss(true, -7));
Assert.AreEqual(0, new SquaredHingeLoss().Loss(false, -8));
Assert.AreEqual(2, new SquaredHingeLoss().Loss(false, 1));
Assert.AreEqual(0.5, new SquaredHingeLoss().Loss(true, 0));
Assert.AreEqual(0.5, new SquaredHingeLoss().Loss(false, 0));
}
public static void test3()
{
var poly2 = CreateFunc(1, 1);
Random rnd = new Random();
var pos = Enumerable.Range(0, 20).Select(x => new double [] { x, poly2(x) + rnd.NextDouble() }).ToArray();
double[] inputs = pos.Select(x => x[0]).ToArray();
double[] outputs = pos.Select(x => x[1]).ToArray();
var ls = new PolynomialLeastSquares()
{
Degree = 2
};
PolynomialRegression poly = ls.Learn(inputs, outputs);
double a = poly.Weights[0]; // a = 0
double b = poly.Weights[1]; // b = 0
double c = poly.Intercept; // c = 1
double[] predicted = poly.Transform(inputs);
double error = new SquareLoss(outputs).Loss(predicted);
var ols = new OrdinaryLeastSquares();
SimpleLinearRegression mul = ols.Learn(inputs, outputs);
double a1 = mul.Slope; // a = 0
double b1 = mul.Intercept; // b = 0
double[] simplepredict = mul.Transform(inputs);
double erroe2 = new SquaredHingeLoss(outputs).Loss(simplepredict);
Console.WriteLine("Done");
}
