/// <inheritdoc /> public ClusteringResult <TInstance> GetClustering(ClusterSet <TInstance> clusterSet) => this.GetClustering(clusterSet, clusterSet.Dissimilarity);
/// <inheritdoc />
public ClusteringResult <TInstance> GetClustering(IEnumerable <Cluster <TInstance> > clusters,
double dissimilarity = 0d)
{
// initializes elements
var currentClusters = clusters.ToArray();
this._clusters = new Cluster <TInstance> [currentClusters.Length * 2 - 1];
this._dissimilarities = new double[currentClusters.Length * 2 - 1][];
this._curClusterCount = 0;
// calculates initial dissimilarities
foreach (var cluster in currentClusters)
{
this._clusters[this._curClusterCount] = cluster;
this.UpdateDissimilarities();
this._curClusterCount++;
}
var clustering = new ClusteringResult <TInstance>(currentClusters.Length)
{
[0] = new ClusterSet <TInstance>(currentClusters, dissimilarity)
};
var numSteps = currentClusters.Length;
for (var i = 1; i < numSteps; i++)
{
// gets minimal dissimilarity between a pair of existing clusters
var minDissimilarity = this.GetMinDissimilarity(out var clusterIdx1, out var clusterIdx2);
// gets a copy of previous clusters, removes new cluster elements
var cluster1 = this._clusters[clusterIdx1];
var cluster2 = this._clusters[clusterIdx2];
var newClusters = new Cluster <TInstance> [currentClusters.Length - 1];
var idx = 0;
foreach (var cluster in currentClusters)
{
if (!cluster.Equals(cluster1) && !cluster.Equals(cluster2))
{
newClusters[idx++] = cluster;
}
}
this._clusters[clusterIdx1] = null;
this._clusters[clusterIdx2] = null;
// creates a new cluster from the union of closest clusters (save reference to parents)
var newCluster = new Cluster <TInstance>(cluster1, cluster2, minDissimilarity);
// adds cluster to list and calculates distance to all others
newClusters[idx] = this._clusters[this._curClusterCount] = newCluster;
this.UpdateDissimilarities();
this._curClusterCount++;
// updates global list of clusters
currentClusters = newClusters;
clustering[i] = new ClusterSet <TInstance>(currentClusters, minDissimilarity);
}
this._clusters = null;
this._dissimilarities = null;
return(clustering);
}
/// <summary>
/// Creates a new <see cref="ClusterSetEvaluation{TInstance}" />.
/// </summary>
/// <param name="clusterSet">The cluster-set that was evaluated.</param>
/// <param name="evaluationValue">The value of the evaluation.</param>
public ClusterSetEvaluation(ClusterSet <TInstance> clusterSet, double evaluationValue)
{
this.ClusterSet = clusterSet;
this.EvaluationValue = evaluationValue;
}
