Generate() public method

Generates.
Thrown when the requested operation is invalid.
public Generate ( Matrix X, Vector y ) : IModel
X Matrix The Matrix to process.
y numl.Math.LinearAlgebra.Vector The Vector to process.
return IModel
DecisionTreeGenerator Class Documentation
Beispiel #1
0
        public void ArbitraryPrediction_Test_With_Named_Iterator()
        {
            var data = ArbitraryPrediction.GetDataUsingNamedIterator();
            var description = Descriptor.Create<ArbitraryPrediction>();
            var generator = new DecisionTreeGenerator(50);
            var model = generator.Generate(description, data);

            ArbitraryPrediction minimumPredictionValue = new ArbitraryPrediction
            {
                FirstTestFeature = 1.0m,
                SecondTestFeature = 10.0m,
                ThirdTestFeature = 1.2m
            };

            ArbitraryPrediction maximumPredictionValue = new ArbitraryPrediction
            {
                FirstTestFeature = 1.0m,
                SecondTestFeature = 57.0m,
                ThirdTestFeature = 1.2m
            };

            var expectedMinimum = model.Predict<ArbitraryPrediction>(minimumPredictionValue).OutcomeLabel;
            var expectedMaximum = model.Predict<ArbitraryPrediction>(maximumPredictionValue).OutcomeLabel;

            Assert.AreEqual(ArbitraryPrediction.PredictionLabel.Minimum, expectedMinimum);
            Assert.AreEqual(ArbitraryPrediction.PredictionLabel.Maximum, expectedMaximum);
        }
Beispiel #2
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        public void Save_And_Load_Iris_DT()
        {
            var data = Iris.Load();
            var description = Descriptor.Create<Iris>();
            var generator = new DecisionTreeGenerator(50);
            var model = generator.Generate(description, data) as DecisionTreeModel;

            Serialize(model);
            var lmodel = Deserialize<DecisionTreeModel>();
            Assert.AreEqual(model.Hint, lmodel.Hint);
            AreEqual(model.Tree, lmodel.Tree, false);
        }
Beispiel #3
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        public void Save_And_Load_HouseDT()
        {
            var data = House.GetData();

            var description = Descriptor.Create<House>();
            var generator = new DecisionTreeGenerator { Depth = 50 };
            var model = generator.Generate(description, data) as DecisionTreeModel;

            Serialize(model);

            var lmodel = Deserialize<DecisionTreeModel>();
            Assert.AreEqual(model.Hint, lmodel.Hint);
            AreEqual(model.Tree, lmodel.Tree, false);
        }