public void TestKnn()
{
var knn = new Knn();
var knnParameter = new KnnParameter(1, 3, new EuclidianDistance());
var pca = new Pca(iris);
pca.Convert();
knn.Train(iris.GetInstanceList(), knnParameter);
Assert.AreEqual(4.00, 100 * knn.Test(iris.GetInstanceList()).GetErrorRate(), 0.01);
pca = new Pca(bupa);
pca.Convert();
knn.Train(bupa.GetInstanceList(), knnParameter);
Assert.AreEqual(19.13, 100 * knn.Test(bupa.GetInstanceList()).GetErrorRate(), 0.01);
pca = new Pca(dermatology);
pca.Convert();
knn.Train(dermatology.GetInstanceList(), knnParameter);
Assert.AreEqual(3.28, 100 * knn.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);
}
