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);
}
