/// <summary>
/// Construct the clusters objects.
/// </summary>
/// <param name="k">The number of clusters to have.</param>
/// <param name="observations">The observations.</param>
public Clusters(int k, IMLDataSet observations)
{
_clustersHash = new Dictionary <IMLDataPair, int>();
_clusters = new List <ICollection <IMLDataPair> >();
IList list = new List <IMLDataPair>();
foreach (IMLDataPair pair in observations)
{
list.Add(pair);
}
var kmc = new KMeansUtil <IMLDataPair>(k, list);
kmc.Process();
for (int i = 0; i < k; i++)
{
ICollection <IMLDataPair> cluster = kmc.Get(i);
_clusters.Add(cluster);
foreach (IMLDataPair element in cluster)
{
_clustersHash[element] = i;
}
}
}
/// <summary>
/// Perform a single training iteration.
/// </summary>
public void Iteration()
{
_kmeans.Process();
_clusters = new IMLCluster[_k];
for (int i = 0; i < _k; i++)
{
_clusters[i] = new BasicCluster(_kmeans.GetCluster(i));
}
}
/// <summary>
/// Construct the clusters objects.
/// </summary>
/// <param name="k">The number of clusters to have.</param>
/// <param name="observations">The observations.</param>
public Clusters(int k, IMLDataSet observations)
{
_clustersHash = new Dictionary<IMLDataPair, int>();
_clusters = new List<ICollection<IMLDataPair>>();
IList list = new List<IMLDataPair>();
foreach (IMLDataPair pair in observations)
{
list.Add(pair);
}
var kmc = new KMeansUtil<IMLDataPair>(k, list);
kmc.Process();
for (int i = 0; i < k; i++)
{
ICollection<IMLDataPair> cluster = kmc.Get(i);
_clusters.Add(cluster);
foreach (IMLDataPair element in cluster)
{
_clustersHash[element] = i;
}
}
}
