public void updatecentroid()
{
Dictionary <int, float> averages = new Dictionary <int, float>();
int usercount = 0;
foreach (UserForKMeansWine user in clustermembers)
{
usercount++;
foreach (KeyValuePair <int, Boolean> rating in user.transactions)
{
if (!averages.ContainsKey(rating.Key))
{
averages.Add(rating.Key, Convert.ToInt16(rating.Value));
}
else
{
averages[rating.Key] = (averages[rating.Key] + Convert.ToInt16(rating.Value));
}
}
}
Dictionary <int, Boolean> newcentroidcoords = new Dictionary <int, bool>();
foreach (KeyValuePair <int, float> pair in averages)
{
Boolean result = (Math.Round(pair.Value / usercount) == 1);
newcentroidcoords.Add(pair.Key, result);
}
currentcentroid = new UserForKMeansWine(int.MaxValue);
currentcentroid.transactions = newcentroidcoords;
}
public float distancebetweenthisanduser(UserForKMeansWine user2)
{
float[] set1 = new float[32];
float[] set2 = new float[32];
foreach (KeyValuePair <int, Boolean> transaction in transactions)
{
set1[transaction.Key] = Convert.ToInt16(transactions[transaction.Key]);
set2[transaction.Key] = Convert.ToInt16(user2.transactions[transaction.Key]);
}
return(Clustering.calculateEuclidianDistance(set1, set2));
}
public static Cluster getClusterWithClosestCentroidForUser(List <Cluster> clusters, UserForKMeansWine user)
{
float lowestdistance = float.PositiveInfinity;
Cluster currentcluster = null;
foreach (Cluster cluster in clusters)
{
float currentdistance = user.distancebetweenthisanduser(cluster.currentcentroid);
if (currentdistance < lowestdistance)
{
lowestdistance = currentdistance;
currentcluster = cluster;
}
}
if (currentcluster == null)
{
throw new ArgumentException("No clusters found to compute");
}
return(currentcluster);
}