private void SelectCentroids(int k, Cluster[] clusters)
{
//seleciona, randomicamente, K padroes como centroides iniciais
Dictionary <int, int> centroidPatternList = new Dictionary <int, int>();
int centroidPattern = -1;
Random random = new Random();
while (centroidPatternList.Count < k)
{
centroidPattern = random.Next(0, patternMatrix.Size() - 1);
if (!centroidPatternList.ContainsKey(centroidPattern))
{
centroidPatternList.Add(centroidPattern, centroidPattern);
}
}
for (int i = 0; i < k; i++)
{
//inicializa os k grupos
clusters[i] = new Cluster();
clusters[i].Id = i;
clusters[i].Centroid = patternMatrix.GetPattern(centroidPatternList.ElementAt(i).Value); // vincula o centroide ao grupo
}
}
public PatternMatrix Transform(HashSet <double[]> dataSet)
{
Pattern patternTemp = new Pattern(); // padrao
PatternMatrix patternMatrix; // matriz de padroes
int index = 0; // identificador do padrao
PatternMatrix zPatternMatrix; //matriz de padroes normalizados
patternMatrix = new PatternMatrix();
zPatternMatrix = new PatternMatrix();
foreach (var item in dataSet)
{
patternTemp = new Pattern();
patternTemp.Id = index;
patternTemp.AddAttributes(item);
patternMatrix.AddPattern(patternTemp);
index++;
}
index = 0;
double attributeSum = 0;
double attributeMean = 0;
double variance = 0;
double attributeStandardDeviation = 0;
double zAttribute = 0;
double[] zpatternAttributes = new double[patternTemp.GetDimension()];
Pattern zPattern; //armazena o valor normalizado do padrao
foreach (Pattern pattern in patternMatrix)
{
for (int i = 0; i < pattern.GetDimension(); i++)
{
foreach (Pattern patternx in patternMatrix)
{
attributeSum += patternx.GetAttribute(i);
}
// calcula a media do atributo
attributeMean = attributeSum / patternMatrix.Size();
attributeSum = 0;
foreach (Pattern patterny in patternMatrix)
{
variance += Math.Pow((patterny.GetAttribute(i) - attributeMean), 2);
}
// calcula a variancia do atributo
variance = variance / patternMatrix.Size();
attributeStandardDeviation = Math.Sqrt(variance); // o desvio padrao eh a raiz quadrada da variancia
zAttribute = (pattern.GetAttribute(i) - attributeMean) / attributeStandardDeviation; //atributo normalizado
zpatternAttributes[i] = Math.Round(zAttribute, 2);
attributeSum = 0;
attributeMean = 0;
variance = 0;
attributeStandardDeviation = 0;
}
zPattern = new Pattern();
zPattern.AddAttributes(zpatternAttributes);
zPattern.Id = index;
zPatternMatrix.AddPattern(zPattern);
index++;
}
return(zPatternMatrix);
}