static void Main(string[] args)
{
int segmentCount = 5;
int dimensions = 6;
int neighborCount = 5;
Matrix <double> data = ReadData();
PrintAttributeNames();
int totalDimensions = ATTRIBUTE_NAMES.Count;
int segmentSize = data.RowCount / segmentCount;
Console.WriteLine("Duomenys iš failo: \n" + data.ToMatrixString());
Matrix <double> normalizedData = NormalizeData(data);
Console.WriteLine("Normalizuoti duomenys: \n" + normalizedData.ToMatrixString());
Matrix <double> covarienceMatrix = GetCovarianceMatrix(normalizedData);
Console.WriteLine("Kovariacijos matrica: \n" + covarienceMatrix.ToMatrixString());
List <KeyValuePair <double, double> > ftrSortedCovarianceList = GetSortedFullTimeResultCovariance(covarienceMatrix);
PrintCovarianceList(ftrSortedCovarianceList);
Counts totals = CalculateFullTimeResultsTotals(normalizedData);
PrintFullTimeResultsTotals(totals);
kMeansClustering clustering = new kMeansClustering(normalizedData, 3);
clustering.Cluster();
/* while (dimensions <= totalDimensions)
* {*/
Console.WriteLine("Dimensijų kiekis: {0}", dimensions);
Matrix <double> reducedData = GetReducedMatrix(ftrSortedCovarianceList, normalizedData, dimensions);
Console.WriteLine("Po dimensijų sumažinimo: \n", reducedData.ToMatrixString());
Console.WriteLine("Duomenys po dimensijų sumažinimo: \n" + reducedData.ToMatrixString());
// Kryžminė patikra
for (int i = 0; i < 5; i++)
{
Matrix <double> trainingData = GetTrainingData(reducedData, segmentSize, i);
Matrix <double> testingData = GetTestingData(reducedData, segmentSize, i);
Bayes bayes = new Bayes(trainingData);
bayes.Learn(i + 1);
bayes.TestList(testingData);
/* KNN kNN = new KNN(trainingData, neighborCount);
* kNN.ClassifyList(trainingData, "Apmokymo duomenys", i + 1);
* kNN.ClassifyList(testingData, "Testavimo duomenys");*/
}
/* dimensions += 6;
* }*/
}
public static Counts CalculateFullTimeResultsTotals(Matrix <double> data)
{
Counts totals = new Counts();
for (int i = 0; i < data.RowCount; i++)
{
if (data[i, FTR_COLUMN] == AWAY)
{
totals.awayWinCount++;
}
else if (data[i, FTR_COLUMN] == DRAW)
{
totals.drawCount++;
}
else if (data[i, FTR_COLUMN] == HOME)
{
totals.homeWinCount++;
}
}
return(totals);
}
static void PrintFullTimeResultsTotals(Counts totals)
{
Console.WriteLine("Namų komandos pergalės: {0}", totals.homeWinCount);
Console.WriteLine("Lygiosios: {0}", totals.drawCount);
Console.WriteLine("Išvykos komandos pergalės: {0}", totals.awayWinCount);
}
