/// <summary>
/// Evaluates all given <see cref="ClusterSet{TInstance}" />s according to the given
/// <see cref="IInternalEvaluationCriterion{TInstance}" />.
/// </summary>
/// <param name="clustering">The cluster-sets to be evaluated.</param>
/// <param name="criterion">The criterion used to evaluate the cluster-sets.</param>
/// <param name="maxClusters">The maximum number of clusters allowed for a cluster-set for it to be evaluated.</param>
/// <returns>A list containing the evaluations for each cluster-set.</returns>
/// <typeparam name="TInstance">The type of instance considered.</typeparam>
public static ICollection <ClusterSetEvaluation <TInstance> > EvaluateClustering <TInstance>(
this ClusteringResult <TInstance> clustering, IInternalEvaluationCriterion <TInstance> criterion,
uint maxClusters) where TInstance : IComparable <TInstance>
{
var evals = new List <ClusterSetEvaluation <TInstance> >();
// checks only one cluster allowed
if (maxClusters == 1)
{
evals.Add(new ClusterSetEvaluation <TInstance>(clustering[0], double.NaN));
return(evals);
}
// evaluates all cluster-sets
foreach (var clusterSet in clustering.Reverse())
{
if (clusterSet.Count < 2 || clusterSet.Count > maxClusters)
{
continue;
}
var eval = criterion.Evaluate(clusterSet);
evals.Add(new ClusterSetEvaluation <TInstance>(clusterSet, eval));
}
return(evals);
}
private static void GetBestPartition(
ClusteringResult <DataPoint> clustering,
IInternalEvaluationCriterion <DataPoint> criterion, string criterionName)
{
// gets coeffs for all cluster-sets
var evals = clustering.EvaluateClustering(criterion);
// saves cluster-sets indexes to CSV file
SaveToCsv(evals, Path.GetFullPath(Path.Combine(RESULTS_PATH, $"{criterionName}.csv")), criterionName);
// gets max coeff
var maxEval = new ClusterSetEvaluation <DataPoint>(null, double.MinValue);
foreach (var eval in evals)
{
if (eval.EvaluationValue > maxEval.EvaluationValue)
{
maxEval = eval;
}
}
// prints cluster set info
Console.WriteLine("======================================");
Console.WriteLine($"Max {criterionName}: {maxEval.EvaluationValue:0.00}");
if (maxEval.ClusterSet == null)
{
return;
}
Console.WriteLine(
$"Clusters at distance: {maxEval.ClusterSet.Dissimilarity:0.00} ({maxEval.ClusterSet.Count})");
foreach (var cluster in maxEval.ClusterSet)
{
Console.WriteLine($" - {cluster}");
}
}
/// <summary>
/// Evaluates all given <see cref="ClusterSet{TInstance}" />s according to the given
/// <see cref="IInternalEvaluationCriterion{TInstance}" />. The maximum number of clusters allowed in a cluster-set for
/// it to be evaluated corresponds to sqrt(N/2), where N is the total number of instances clustered.
/// </summary>
/// <param name="clustering">The cluster-sets to be evaluated.</param>
/// <param name="criterion">The criterion used to evaluate the cluster-sets.</param>
/// <returns>A list containing the evaluations for each cluster-set.</returns>
/// <typeparam name="TInstance">The type of instance considered.</typeparam>
public static ICollection <ClusterSetEvaluation <TInstance> > EvaluateClustering <TInstance>(
this ClusteringResult <TInstance> clustering, IInternalEvaluationCriterion <TInstance> criterion)
where TInstance : IComparable <TInstance> =>
EvaluateClustering(clustering, criterion, (uint)Math.Sqrt(clustering.Count / 2d));
