Accord.Tests.MachineLearning.C45LearningTest.iris_new_method_create_tree C# (CSharp) 메소드

        public void iris_new_method_create_tree()
        {
            string[][] text = Resources.iris_data.Split(new[] { '\n' }, StringSplitOptions.RemoveEmptyEntries).Apply(x => x.Split(','));

            double[][] inputs = text.GetColumns(0, 1, 2, 3).To<double[][]>();

            string[] labels = text.GetColumn(4);

            var codebook = new Codification("Output", labels);

            int[] outputs = codebook.Translate("Output", labels);

            DecisionVariable[] features =
            {
                new DecisionVariable("sepal length", DecisionVariableKind.Continuous), 
                new DecisionVariable("sepal width", DecisionVariableKind.Continuous), 
                new DecisionVariable("petal length", DecisionVariableKind.Continuous), 
                new DecisionVariable("petal width", DecisionVariableKind.Continuous), 
            };

            var teacher = new C45Learning(features);

            var tree = teacher.Learn(inputs, outputs);
            Assert.AreEqual(4, tree.NumberOfInputs);
            Assert.AreEqual(3, tree.NumberOfOutputs);


            // To get the estimated class labels, we can use
            int[] predicted = tree.Decide(inputs);

            // And the classification error can be computed as 
            double error = new ZeroOneLoss(outputs) // 0.0266
            {
                Mean = true
            }.Loss(tree.Decide(inputs));

            // Moreover, we may decide to convert our tree to a set of rules:
            DecisionSet rules = tree.ToRules();

            // And using the codebook, we can inspect the tree reasoning:
            string ruleText = rules.ToString(codebook, "Output",
                System.Globalization.CultureInfo.InvariantCulture);

            // The output is:
            string expected = @"Iris-setosa =: (petal length <= 2.45)
Iris-versicolor =: (petal length > 2.45) && (petal width <= 1.75) && (sepal length <= 7.05) && (sepal width <= 2.85)
Iris-versicolor =: (petal length > 2.45) && (petal width <= 1.75) && (sepal length <= 7.05) && (sepal width > 2.85)
Iris-versicolor =: (petal length > 2.45) && (petal width > 1.75) && (sepal length <= 5.95) && (sepal width > 3.05)
Iris-virginica =: (petal length > 2.45) && (petal width <= 1.75) && (sepal length > 7.05)
Iris-virginica =: (petal length > 2.45) && (petal width > 1.75) && (sepal length > 5.95)
Iris-virginica =: (petal length > 2.45) && (petal width > 1.75) && (sepal length <= 5.95) && (sepal width <= 3.05)
";

            Assert.AreEqual(0.026666666666666668, error, 1e-10);

            double newError = ComputeError(rules, inputs, outputs);
            Assert.AreEqual(0.026666666666666668, newError, 1e-10);
            Assert.AreEqual(expected, ruleText);
        }