private bool CalculateClusterMembership(List <INode> clusters, List <INode> classes)
{
bool changed = false;
for (int i = 0; i < classes.Count; i++)
{
int newClusterId = -1;
double min_distance = -1;
double distance = -1;
for (int k = 0; k < ClusterNumber; k++)
{
// Distance - it is similarity of entities
// Max similarity means that distance between entities is minimal
distance = NodeSimilarity.JaccardCoefficient(clusters[k], classes[i]);
if (newClusterId == -1 || distance > min_distance)
{
newClusterId = k;
min_distance = distance;
}
}
// Mark class to move into another cluster
if (newClusterId != classes[i].ClusterId)
{
classes[i].ClusterId = newClusterId;
changed = true;
}
}
return(changed);
}
private bool ClusteringStep(List <INode> data, ref int clusterCounter)
{
double[,] distances = new double[data.Count, data.Count];
double minimal_distance = -1;
int firstNodeToJoinIndex = -1;
int secondNodeToJoinIndex = -1;
for (int i = 0; i < data.Count; i++)
{
for (int j = i; j < data.Count; j++)
{
if (i != j)
{
double distance = NodeSimilarity.JaccardCoefficient(data[i], data[j]);
distances[i, j] = distance;
// Max distance means that object are most similar
if (minimal_distance == -1 || distance > minimal_distance)
{
minimal_distance = distance;
firstNodeToJoinIndex = i;
secondNodeToJoinIndex = j;
}
}
}
}
// No joined clusters
if (minimal_distance == -1)
{
return(false);
}
INode firstNode = data[firstNodeToJoinIndex];
INode secondNode = data[secondNodeToJoinIndex];
string clusterName = "Cluster #" + clusterCounter++;
// Join clusters and remove them from list
INode joinedNode = new Node(clusterName, firstNode, secondNode);
data.RemoveAt(firstNodeToJoinIndex);
if (firstNodeToJoinIndex < secondNodeToJoinIndex)
{
secondNodeToJoinIndex--;
}
data.RemoveAt(secondNodeToJoinIndex);
data.Add(joinedNode);
return(true);
}