public static List <DocumentVector> GetSeedPoints2v(List <DocumentVector> docCollection, int k)
{
List <DocumentVector> seedPoints = new List <DocumentVector>(k);
DocDetails docDetails;
List <DocDetails> docDetailsList = new List <DocDetails>();
int index = 0;
int firstIndex = KMeansPlus.GenerateRandomNumber(0, docCollection.Count);
DocumentVector FirstPoint = docCollection[firstIndex];
seedPoints.Add(FirstPoint);
for (int i = 0; i < k - 1; i++)
{
if (seedPoints.Count >= 2)
{
DocDetails minpd = GetMinimalPointDistance(docDetailsList);
index = GetWeightedProbDist(minpd.Weights, minpd.Sum);
DocumentVector SubsequentPoint = docCollection[index];
docDetails = new DocDetails();
docDetails = GetAllDetails(docCollection, SubsequentPoint, docDetails);
docDetailsList.Add(docDetails);
}
else
{
docDetails = new DocDetails();
docDetails = GetAllDetails(docCollection, FirstPoint, docDetails);
docDetailsList.Add(docDetails);
index = GetWeightedProbDist(docDetails.Weights, docDetails.Sum);
DocumentVector SecondPoint = docCollection[index];
seedPoints.Add(SecondPoint);
docDetails = new DocDetails();
docDetails = GetAllDetails(docCollection, SecondPoint, docDetails);
docDetailsList.Add(docDetails);
}
}
return(seedPoints);
}
private static DocDetails GetAllDetails(List <DocumentVector> docCollection, DocumentVector seedPoint, DocDetails docDetails)
{
float[] Weights = new float[docCollection.Count];
float minD = float.MaxValue;
float Sum = 0;
int i = 0;
foreach (DocumentVector point in docCollection)
{
if (point == seedPoint) //Delta is 0
{
continue;
}
Weights[i] = KMeansPlus.GetEucliedeanDistance(point, seedPoint);
Sum += Weights[i];
if (Weights[i] < minD)
{
minD = Weights[i];
}
i++;
}
docDetails.SeedDocVect = seedPoint;
docDetails.Weights = Weights;
docDetails.Sum = Sum;
docDetails.MinD = minD;
return(docDetails);
}
