/// <summary>
/// Generates cluster set using selected datapoints
/// </summary>
/// <param name="isChosen">Is datapoint is chosen</param>
/// <returns></returns>
public ClusterSet GetClusterSet(bool[] isChosen)
{
var clusterSet = new ClusterSet();
// generates datapoint
for (var i = 0; i < Rows.Count; i++)
{
var dataPoint = new DataPoint {
Id = i
};
// gets all points of datapoint
for (var j = StringHeadings.Length; j < FieldsCount; j++)
{
dataPoint.Add(double.Parse(Rows[i][j]));
}
// new cluster
var cluster = new Cluster {
Id = i
};
cluster.AddDataPoint(dataPoint);
cluster.SetCentroid();
// add to set
clusterSet.AddCluster(cluster);
}
return(clusterSet);
}
/// <summary>
/// Builds the hierarchical clustering.
/// </summary>
/// <param name="indexNewCluster">The index new cluster.</param>
/// <param name="k">The k.</param>
/// <param name="isWithIndex">if set to <c>true</c> [is with index].</param>
private void BuildHierarchicalClustering(int indexNewCluster, int k, bool isWithIndex = false)
{
ClusterPair closestClusterPair = _dissimilarityMatrix.GetClosestClusterPair(); // gets the clusterpair with minimal distance
// creates new cluster by merging clusters from closestClusterPair
Cluster newCluster = new Cluster();
newCluster.AddSubCluster(closestClusterPair.Cluster1);
newCluster.AddSubCluster(closestClusterPair.Cluster2);
newCluster.Id = indexNewCluster;
newCluster.SetCentroid();
// removes cluster pair from _clusters
_clusters.RemoveClusterPair(closestClusterPair);
_UpdateDissimilarityMatrix(newCluster);
// add new cluster to _clusters
_clusters.AddCluster(newCluster);
if (isWithIndex) // checks is executed for calculating CH index
{
_chValue.Add(GetCHIndex()); // adds index to array of CH values
_chIndex.Add(_clusters.ClustersList.Count); // adds number of clusters for current CH value
}
// exit point of algorithm (Where _clusters count is equal to k)
if (_clusters.Count > k)
{
BuildHierarchicalClustering(indexNewCluster + 1, k, isWithIndex);
}
}
