public void TestTrain()
{
var linearPerceptron = new LinearPerceptron();
var linearPerceptronParameter = new LinearPerceptronParameter(1, 0.1, 0.99, 0.2, 100);
linearPerceptron.Train(iris.GetInstanceList(), linearPerceptronParameter);
Assert.AreEqual(8.67, 100 * linearPerceptron.Test(iris.GetInstanceList()).GetErrorRate(), 0.01);
linearPerceptronParameter = new LinearPerceptronParameter(1, 0.001, 0.99, 0.2, 100);
linearPerceptron.Train(bupa.GetInstanceList(), linearPerceptronParameter);
Assert.AreEqual(31.88, 100 * linearPerceptron.Test(bupa.GetInstanceList()).GetErrorRate(), 0.01);
linearPerceptronParameter = new LinearPerceptronParameter(1, 0.1, 0.99, 0.2, 100);
linearPerceptron.Train(dermatology.GetInstanceList(), linearPerceptronParameter);
Assert.AreEqual(3.28, 100 * linearPerceptron.Test(dermatology.GetInstanceList()).GetErrorRate(), 0.01);
}
public void TestLinearPerceptron()
{
var linearPerceptron = new LinearPerceptron();
var linearPerceptronParameter = new LinearPerceptronParameter(1, 0.1, 0.99, 0.2, 100);
var discreteToIndexed = new DiscreteToIndexed(car);
discreteToIndexed.Convert();
linearPerceptron.Train(car.GetInstanceList(), linearPerceptronParameter);
Assert.AreEqual(8.80, 100 * linearPerceptron.Test(car.GetInstanceList()).GetErrorRate(), 0.01);
discreteToIndexed = new DiscreteToIndexed(tictactoe);
discreteToIndexed.Convert();
linearPerceptron.Train(tictactoe.GetInstanceList(), linearPerceptronParameter);
Assert.AreEqual(1.67, 100 * linearPerceptron.Test(tictactoe.GetInstanceList()).GetErrorRate(), 0.01);
}
public void TestLinearPerceptron()
{
var linearPerceptron = new LinearPerceptron();
var linearPerceptronParameter = new LinearPerceptronParameter(1, 0.1, 0.99, 0.2, 100);
var normalize = new Normalize(iris);
normalize.Convert();
linearPerceptron.Train(iris.GetInstanceList(), linearPerceptronParameter);
Assert.AreEqual(2.67, 100 * linearPerceptron.Test(iris.GetInstanceList()).GetErrorRate(), 0.01);
normalize = new Normalize(bupa);
normalize.Convert();
linearPerceptron.Train(bupa.GetInstanceList(), linearPerceptronParameter);
Assert.AreEqual(31.59, 100 * linearPerceptron.Test(bupa.GetInstanceList()).GetErrorRate(), 0.01);
normalize = new Normalize(dermatology);
normalize.Convert();
linearPerceptron.Train(dermatology.GetInstanceList(), linearPerceptronParameter);
Assert.AreEqual(1.09, 100 * linearPerceptron.Test(dermatology.GetInstanceList()).GetErrorRate(), 0.01);
}
public void TestLinearPerceptron()
{
var linearPerceptron = new LinearPerceptron();
var linearPerceptronParameter = new LinearPerceptronParameter(1, 0.1, 0.99, 0.2, 100);
var pca = new Pca(iris);
pca.Convert();
linearPerceptron.Train(iris.GetInstanceList(), linearPerceptronParameter);
Assert.AreEqual(8.67, 100 * linearPerceptron.Test(iris.GetInstanceList()).GetErrorRate(), 0.01);
linearPerceptronParameter = new LinearPerceptronParameter(1, 0.01, 0.99, 0.2, 100);
pca = new Pca(bupa);
pca.Convert();
linearPerceptron.Train(bupa.GetInstanceList(), linearPerceptronParameter);
Assert.AreEqual(42.03, 100 * linearPerceptron.Test(bupa.GetInstanceList()).GetErrorRate(), 0.01);
pca = new Pca(dermatology);
pca.Convert();
linearPerceptron.Train(dermatology.GetInstanceList(), linearPerceptronParameter);
Assert.AreEqual(1.64, 100 * linearPerceptron.Test(dermatology.GetInstanceList()).GetErrorRate(), 0.01);
}
