public void Iris_Naive_Bayes_Save_And_Load_Test() { var data = Iris.Load(); var description = Descriptor.Create <Iris>(); var generator = new NaiveBayesGenerator(2); var model = generator.Generate(description, data); Serialize(model); var lmodel = Deserialize <NaiveBayesModel>(); }
public void Tennis_Naive_Bayes_Save_And_Load_Test() { var data = Tennis.GetData(); var description = Descriptor.Create <Tennis>(); var generator = new NaiveBayesGenerator(2); var model = generator.Generate(description, data) as NaiveBayesModel; Serialize(model); var lmodel = Deserialize <NaiveBayesModel>(); Assert.AreEqual(model.Root, lmodel.Root); }
public void Iris_Naive_Bayes_Save_And_Load_Test_Json() { var data = Iris.Load(); var description = Descriptor.Create <Iris>(); var generator = new NaiveBayesGenerator(2); var model = generator.Generate(description, data) as NaiveBayesModel; var file = GetPath(); Register.Type <Iris>(); var lmodel = SaveAndLoadJson(model); Assert.Equal(model.Root, lmodel.Root); }
public override void CreateClassifier() { // this.Normalizator = new Normalizator.Normalizator(this.Stats); // this.Stats = this.Normalizator.Normalize(this.Stats); //var testSet = this.ModifyStatsByWeights(stats); //vytvoreni modelu klasifikace... var testSet = this.Stats; var descriptor = Descriptor.Create <FeatureVector>(); var modelBay = new NaiveBayesGenerator(descriptor.VectorLength); modelBay.Generate((IEnumerable <object>)testSet); var learnBay = Learner.Learn(testSet, 0.9, 100, modelBay); //learnBay.Model.Save("model4"); //learnBay = new LearningModel(); //this.ClassifierModel = learnBay.Model.Load("model2"); this.ClassifierModel = learnBay.Model; }
public void Main_Naive_Bayes_Test() { var data = Tennis.GetData(); var description = Descriptor.Create <Tennis>(); var generator = new NaiveBayesGenerator(2); var model = generator.Generate(description, data); Tennis t = new Tennis { Humidity = Humidity.Normal, Outlook = Outlook.Overcast, Temperature = Temperature.Cool, Windy = true }; model.Predict <Tennis>(t); Assert.IsTrue(t.Play); }
public void Iris_DT_and_Prediction() { var data = Iris.Load(); var description = Descriptor.Create <Iris>(); var generator = new NaiveBayesGenerator(2); var model = generator.Generate(description, data); // should be Iris-Setosa Iris iris = new Iris { SepalLength = 2.1m, SepalWidth = 2.2m, PetalWidth = 0.5m, PetalLength = 2.3m, }; iris = model.Predict <Iris>(iris); Assert.AreEqual("Iris-setosa".Sanitize(), iris.Class); }