public void RemoveClusterPair(ClusterNodePair clusterPair)
{
double outvalue;
if (distanceMatrix.ContainsKey(clusterPair))
{
distanceMatrix.TryRemove(clusterPair, out outvalue);
}
else
{
distanceMatrix.TryRemove(new ClusterNodePair(clusterPair.Cluster2, clusterPair.Cluster1), out outvalue);
}
}
private void BuildHierarchicalClustering(int indexNewNode, ClusterDistance.Strategy strategy, int k)
{
ClusterNodePair closestClusterPair = dissimilarityMatrix.GetClosestClusterPair();
ClusterNode newNode = new ClusterNode();
newNode.Add(closestClusterPair.Cluster1);
newNode.Add(closestClusterPair.Cluster2);
newNode.Id = indexNewNode;
newNode.Distance = dissimilarityMatrix.ReturnClusterPairDistance(closestClusterPair);
newNode.UpdateTotalLeafs();
nodeCollection.Remove(closestClusterPair.Cluster1);
nodeCollection.Remove(closestClusterPair.Cluster2);
UpdateDissimilarityMatrix(newNode, strategy);
nodeCollection.Add(newNode);
if (nodeCollection.Count > k)
{
BuildHierarchicalClustering(indexNewNode + 1, strategy, k);
}
}
// get the distance value from a cluster pair. THIS METHOD DEPENDS ON THE EqualityComparer IMPLEMENTATION IN ClusterPair CLASS
public double ReturnClusterPairDistance(ClusterNodePair clusterPair)
{
return(distanceMatrix.ContainsKey(clusterPair)
? distanceMatrix[clusterPair]
: distanceMatrix[new ClusterNodePair(clusterPair.Cluster2, clusterPair.Cluster1)]); // Reverse
}
public void AddClusterPairAndDistance(ClusterNodePair clusterPair, double distance)
{
distanceMatrix.TryAdd(clusterPair, distance);
}
