private static double AverageInterDissimilar(double[] currInput, ClusterItem[] cluster, Distance distance)
{
double[] d = new double[cluster.Length];
for (int i = 0; i < d.Length; i++)
{
d[i] = distance.Similarity(currInput, cluster[i].InputVector);
}
return(d.Average());
}
private static double AverageDissimilar(double[] currInput, ClusterItem[] cluster, Distance distance)
{
double[] d = new double[cluster.Length];
for (int i = 0; i < d.Length; i++)
{
d[i] = distance.Similarity(currInput, cluster[i].InputVector);
}
return(d.Sum() / (d.Length - 1)); // remove one element => itself
}
public static double WithinClusterVariance(ClusterItem[][] clusters, double[][] centroids, int numSamples, Distance distance)
{
double var = 0;
for (int i = 0; i < clusters.Length; i++)
{
for (int j = 0; j < clusters[i].Length; j++)
{
var += distance.Similarity(clusters[i][j].InputVector, centroids[clusters[i][j].Label]);
}
}
var = var / numSamples * 1.0;
return(var);
}