public static List <Cluster> initiateClusters(int amount, initialCentrioidSelection selectiontype, Dictionary <int, UserForKMeansWine> users)
{
Random picker = new Random();
List <Cluster> returnlist = new List <Cluster>();
while (amount != 0)
{
Cluster clusterconstruct = new Cluster();
if (selectiontype == initialCentrioidSelection.RandomUser)
{
int randomuser = picker.Next(users.Count);
clusterconstruct.currentcentroid = users[randomuser];
}
returnlist.Add(clusterconstruct);
amount--;
}
return(returnlist);
}
public static Tuple <float, List <Cluster> > kmeaniteration(int clusters, Dictionary <int, UserForKMeansWine> users, initialCentrioidSelection selectiontypes)
{
List <Cluster> listofclusters = initiateClusters(clusters, selectiontypes, users);
foreach (KeyValuePair <int, UserForKMeansWine> user in users)
{
try
{
Cluster usercluster = getClusterWithClosestCentroidForUser(listofclusters, user.Value);
usercluster.clustermembers.Add(user.Value);
}catch (ArgumentException e)
{
System.Console.Out.Write(e.Message);
MessageBox.Show("e.message");
}
}
foreach (Cluster cluster in listofclusters)
{
cluster.updatecentroid();
}
return(new Tuple <float, List <Cluster> >(2f, listofclusters));
}
