static void Main(string[] args)
{
var patientClasses = DataReader.LoadCsv("Data/csvResult.dat");
var patientFeatures = DataReader.LoadCsv("Data/csvFeatures.dat");
ContinousFeaturesRanges.Buckets = 10;
int[] featuresIds = null;// new[] { 4, 5, 6, 20 };
IList <Patient> patients = PatientCreator.Create(patientClasses, patientFeatures, featuresIds);
var crossDataAlgorithm = new CrossDataAlgorithm(patients, 5);
foreach (var confusionMatrixData in crossDataAlgorithm.ConfusionMatrixDatas)
{
ConfusionMatrixCreator.ShowConfusionMatrix(confusionMatrixData);
}
}
public void ConfusionMatrixCreator_TrueClassPatient_ConfusionMatrix()
{
IList <Patient> patients = new List <Patient>
{
new Patient(Classification.Normal, null)
{
BayesClassification = Classification.Normal,
}
};
var cmc = new ConfusionMatrixCreator();
var confM = cmc.CreateConfusionMatrix(patients, 1, Group.A);
Assert.Equal(1, confM.ConfusionMatrix[0, 0]);
}
public CrossDataAlgorithm(IList <Patient> patients, int repetitions)
{
ConfusionMatrixDatas = new List <ConfusionMatrixData>();
ConfusionMatrixCreator = new ConfusionMatrixCreator();
PatientsGroupsList = new List <PatientsGroups>();
for (int i = 0; i < repetitions; i++)
{
PatientsGroupsList.Add(new PatientsGroups(patients));
}
_actualRandomNmb = 0;
foreach (var patientsGroups in PatientsGroupsList)
{
_actualRandomNmb++;
DoubleCrossValidation(patientsGroups);
}
}