Accord.Tests.MachineLearning.CrossvalidationTest.NotEnoughSamplesTest1 C# (CSharp) Method

        public void NotEnoughSamplesTest1()
        {
            Accord.Math.Random.Generator.Seed = 0;

            int[] labels = Matrix.Vector(10, 1).Concatenate(Matrix.Vector(30, 0));

            Vector.Shuffle(labels);

            var crossvalidation = new CrossValidation<MulticlassSupportVectorMachine>(size: 40, folds: 10)
            {
                RunInParallel = false,

                Fitting = (int index, int[] indicesTrain, int[] indicesValidation) =>
                {
                    var labelsValidation = labels.Submatrix(indicesValidation);
                    int countValidation = labelsValidation.Count(x => x == 1);
                    Assert.AreEqual(2, countValidation);

                    var labelsTraining = labels.Submatrix(indicesTrain);
                    int countTraining = labelsTraining.Count(x => x == 1);
                    Assert.AreEqual(9 * 2, countTraining);

                    return new CrossValidationValues<MulticlassSupportVectorMachine>(null, 0, 0);
                }
            };

            bool thrown = false;
            try { crossvalidation.Compute(); }
            catch (Exception) { thrown = true; }
            Assert.IsTrue(thrown);

            crossvalidation = new CrossValidation<MulticlassSupportVectorMachine>(labels, 2, folds: 10)
            {
                RunInParallel = false,

                Fitting = (int index, int[] indicesTrain, int[] indicesValidation) =>
                {
                    var labelsValidation = labels.Submatrix(indicesValidation);
                    int countValidation = labelsValidation.Count(x => x == 1);
                    Assert.AreEqual(1, countValidation);

                    var labelsTraining = labels.Submatrix(indicesTrain);
                    int countTraining = labelsTraining.Count(x => x == 1);
                    Assert.AreEqual(9, countTraining);

                    return new CrossValidationValues<MulticlassSupportVectorMachine>(null, 0, 0);
                }
            };

            crossvalidation.Compute();
        }