public void LoadModelFromFile()
{
string pathFull = System.IO.Path.Combine(Util.GetProjectDir2(), _fileModelIris);
var xgbc = XGBoost.XGBClassifier.LoadClassifierFromFile(pathFull);
///
/// Load testingvectors
///
int noOfClasses = 3;
string filenameTest = "Iris\\Iris.test.data";
iris.Iris[] recordsTest = IrisUtils.LoadIris(filenameTest);
entity.XGVector <iris.Iris>[] vectorsTest = IrisUtils.ConvertFromIrisToFeatureVectors(recordsTest);
entity.XGBArray arrTest = Util.ConvertToXGBArray(vectorsTest);
var outcomeTest = xgbc.Predict(arrTest.Vectors);
for (int index = 0; index < arrTest.Vectors.Length; index++)
{
string sExpected = IrisUtils.ConvertLabelFromNumericToString(arrTest.Labels[index]);
float[] arrResults = new float[]
{
outcomeTest[index * noOfClasses + 0],
outcomeTest[index * noOfClasses + 1],
outcomeTest[index * noOfClasses + 2]
};
float max = arrResults.Max();
int indexWithMaxValue = Util.GetIndexWithMaxValue(arrResults);
string sActualClass = IrisUtils.ConvertLabelFromNumericToString((float)indexWithMaxValue);
Trace.WriteLine($"{index} Expected={sExpected} Actual={sActualClass}");
Assert.AreEqual(sActualClass, sExpected);
}
}
public void BasicLoadData()
{
string filename = "Iris\\Iris.train.data";
iris.Iris[] records = IrisUtils.LoadIris(filename);
entity.XGVector <iris.Iris>[] vectors = IrisUtils.ConvertFromIrisToFeatureVectors(records);
Assert.IsTrue(records.Length >= 140);
}
