public void Logistic_Regression_Test_CostFunction_1()
{
Matrix X = new[, ]
{
{ 1, 1, 1 },
{ 1, 1, 1 },
{ 1, 1, 1 },
{ 8, 1, 6 },
{ 3, 5, 7 },
{ 4, 9, 2 }
};
Vector y = new Vector(new double[] { 1, 0, 1, 0, 1, 0 });
Vector theta = new Vector(new double[] { 0, 1, 0 });
numl.Math.Functions.Cost.ICostFunction logisticCostFunction = new numl.Math.Functions.Cost.LogisticCostFunction();
numl.Math.Functions.Regularization.IRegularizer regularizer = new numl.Math.Functions.Regularization.Regularization();
double cost = logisticCostFunction.ComputeCost(theta.Copy(), X, y, 3, regularizer);
theta = logisticCostFunction.ComputeGradient(theta.Copy(), X, y, 3, regularizer);
Assert.AreEqual(2.2933d, System.Math.Round(cost, 4));
Assert.AreEqual(1.6702d, System.Math.Round(theta[0], 4));
Assert.AreEqual(2.1483d, System.Math.Round(theta[1], 4));
Assert.AreEqual(1.0887d, System.Math.Round(theta[2], 4));
}
public void Logistic_Regression_Test_CostFunction_2_WithoutRegularization()
{
Matrix X = new[, ] {
{ 8, 1, 6 },
{ 3, 5, 7 },
{ 4, 9, 2 }
};
Vector y = new Vector(new double[] { 1, 1, 0 });
Vector theta = new Vector(new double[] { 0, 1, 0 });
numl.Math.Functions.Cost.ICostFunction logisticCostFunction = new numl.Math.Functions.Cost.LogisticCostFunction();
double cost = logisticCostFunction.ComputeCost(theta.Copy(), X, y, 0, null);
theta = logisticCostFunction.ComputeGradient(theta.Copy(), X, y, 0, null);
Assert.AreEqual(3.1067d, System.Math.Round(cost, 4));
Assert.AreEqual(0.6093d, System.Math.Round(theta[0], 4));
Assert.AreEqual(2.8988d, System.Math.Round(theta[1], 4));
Assert.AreEqual(0.1131d, System.Math.Round(theta[2], 4));
}
public void Logistic_Regression_Test_CostFunction_1()
{
Matrix X = new[,]
{{ 1, 1, 1 },
{ 1, 1, 1 },
{ 1, 1, 1 },
{ 8, 1, 6 },
{ 3, 5 ,7 },
{ 4, 9, 2 }};
Vector y = new Vector(new double[] { 1, 0, 1, 0, 1, 0 });
Vector theta = new Vector(new double[] { 0, 1, 0 });
numl.Math.Functions.Cost.ICostFunction logisticCostFunction = new numl.Math.Functions.Cost.LogisticCostFunction();
numl.Math.Functions.Regularization.IRegularizer regularizer = new numl.Math.Functions.Regularization.Regularization();
double cost = logisticCostFunction.ComputeCost(theta.Copy(), X, y, 3, regularizer);
theta = logisticCostFunction.ComputeGradient(theta.Copy(), X, y, 3, regularizer);
Assert.AreEqual(2.2933d, System.Math.Round(cost, 4));
Assert.AreEqual(1.6702d, System.Math.Round(theta[0], 4));
Assert.AreEqual(2.1483d, System.Math.Round(theta[1], 4));
Assert.AreEqual(1.0887d, System.Math.Round(theta[2], 4));
}
public void Logistic_Regression_Test_CostFunction_2_WithoutRegularization()
{
Matrix X = new[,] {
{ 8, 1, 6 },
{ 3, 5 ,7 },
{ 4, 9, 2 }};
Vector y = new Vector(new double[] { 1, 1, 0 });
Vector theta = new Vector(new double[] { 0, 1, 0 });
numl.Math.Functions.Cost.ICostFunction logisticCostFunction = new numl.Math.Functions.Cost.LogisticCostFunction();
double cost = logisticCostFunction.ComputeCost(theta.Copy(), X, y, 0, null);
theta = logisticCostFunction.ComputeGradient(theta.Copy(), X, y, 0, null);
Assert.AreEqual(3.1067d, System.Math.Round(cost, 4));
Assert.AreEqual(0.6093d, System.Math.Round(theta[0], 4));
Assert.AreEqual(2.8988d, System.Math.Round(theta[1], 4));
Assert.AreEqual(0.1131d, System.Math.Round(theta[2], 4));
}
