Accord.Tests.MachineLearning.ErrorBasedpruningTest.RunTest C# (CSharp) Метод

        public void RunTest()
        {
            double[][] inputs;
            int[] outputs;

            int training = 6000;
            DecisionTree tree = ReducedErrorPruningTest.createNurseryExample(out inputs, out outputs, training);

            int nodeCount = 0;
            foreach (var node in tree)
                nodeCount++;

            var pruningInputs = inputs.Submatrix(training, inputs.Length - 1);
            var pruningOutputs = outputs.Submatrix(training, inputs.Length - 1);
            ErrorBasedPruning prune = new ErrorBasedPruning(tree, pruningInputs, pruningOutputs);

            prune.Threshold = 0.1;

            double lastError, error = Double.PositiveInfinity;
            do
            {
                lastError = error;
                error = prune.Run();
            } while (error < lastError);

            int nodeCount2 = 0;
            foreach (var node in tree)
                nodeCount2++;

            Assert.AreEqual(0.28922413793103446, error);
            Assert.AreEqual(447, nodeCount);
            Assert.AreEqual(424, nodeCount2);
        }