/// <summary>
/// Compare two classifications and get a metric that identifies how similar they are.
///
/// Consider this the gold standard categorization and alternatePartition the unattended clustering.
/// (It doesn't matter, as the results are symmetrical.)
/// </summary>
/// <param name="alternatePartition">The unattended clustering.</param>
/// <param name="alpha">Determines how to weight the Precision and Recall.
/// The default value of 0.5 works well for most situations and evenly balances Precision and Recall.
/// Must be between 0 and 1. </param>
/// <returns>The metric. Casting it to a double (or calling BCubed) will retrieve a numerical measure.
/// If that value is 1.0, the classifications are identical.
/// </returns>
public ClusterMetric <TPoint, TLabel> Compare(Classification <TPoint, TLabel> alternatePartition, double alpha = 0.5)
{
var category = this;
var cluster = alternatePartition;
ClusterMetric <TPoint, TLabel> metric;
// IsSimilar is fast, but less precise. If it says the Classifications have identical clustering, they do,
// but if they do not, we need to figure out how bad they match and need to create a real ClusterMetric.
if (category.IsSimilarTo(cluster))
{
metric = new ClusterMetric <TPoint, TLabel>();
}
else
{
metric = new ClusterMetric <TPoint, TLabel>(
Points().ToList(),
label => category.LabelToPoints[label],
label => cluster.LabelToPoints[label],
point => category.PointToLabel[point],
point => cluster.PointToLabel[point],
alpha
);
}
metric.Measure();
return(metric);
}
/// <summary>
/// Compare the initial and final classifications and set MeasuredChange.
/// </summary>
/// <returns>The result of the comparison.</returns>
ClusterMetric <UnsignedPoint, string> RecordResult()
{
// Compute the BCubed score between the initial and final classification IF there was an initial classification.
if (InitialClassification.NumPartitions != InitialClassification.NumPoints)
{
Timer.Start("Compare classifications");
MeasuredChange = CompareClassifications();
Timer.Stop("Compare classifications");
// Write comparison to the log.
Logger.Info($"Comparison between initial and final classification: {MeasuredChange}. Acceptable: {Configuration.AcceptableBCubed}");
}
else
{
MeasuredChange = new ClusterMetric <UnsignedPoint, string>()
{
Precision = 0,
Recall = 0
};
}
return(MeasuredChange);
}