/// <summary>
/// recalculates the centroid of a cluster based on its current members
/// </summary>
public void ReCalculateCentroid()
{
int maxFeature = this.currentCentroid.ExpectedNoOfFeatures;
if (this.members.Count == 0)//implement better check #### TO-DOOOO
{
}
else
{
//calculate the mean value for each attribute of the current centroid
Observation newCentroid = new Observation(maxFeature);
newCentroid = members.ElementAt(0);
for (int i = 0; i < maxFeature; i++)
{
for (int j = 1; j < this.members.Count; j++)
{
newCentroid.ReplaceFeature(i, newCentroid.GetFeature(i).Sum(this.members.ElementAt(j).GetFeature(i)));
}
newCentroid.ReplaceFeature(i, newCentroid.GetFeature(i).Average(this.members.Count));
}
this.prevCentroid = currentCentroid;
this.currentCentroid = newCentroid;
}
}
public int GetDistance(Observation observation)
{
//#### CONSIDER NORMALIZING in KMEANS
int runningSum = 0;
for (int i = 0; i < this.features.Count; i++)
{
runningSum += this.features.ElementAt(i).CalculateDistance(observation.GetFeature(i));
}
return(runningSum);
}