public static void ShowClusters(BaseKMeans kMeans)
{
Console.WriteLine();
Console.WriteLine($"Clusters count: {kMeans.ClustersCount}");
Console.WriteLine();
Console.WriteLine($"Centroids:");
kMeans.Centroids.ForEach(Console.WriteLine);
ShowSongsByClusters(kMeans);
}
static List <Prediction> MakePredictions(BaseKMeans model, List <Song> analyzingSongs)
{
SongSuccessPredictor predictor = new SongSuccessPredictor(model, model.DistanceFunc);
predictor.PrepareData();
List <Prediction> predictions = analyzingSongs.Select(predictor.PredictSuccess).ToList();
// Console.WriteLine("Predictions:");
// predictions.ForEach(Console.WriteLine);
return(predictions);
}
double AnalyzeSilhouetteCoef(List <AnalyzedSong> analyzedSongs, BaseKMeans model)
{
double silhouetteCoefMean = 0.0;
foreach (AnalyzedSong analyzedSong in AnalyzedSongs)
{
int nearestClusterIndex = model.GetNearestClusterIndex(analyzedSong.AssociatedSong);
int secondNearestClusterIndex = model.GetSecondNearestClusterIndex(analyzedSong.AssociatedSong);
List <Song> nearestCluster = model.Clusters[nearestClusterIndex];
List <Song> secondNearestCluster = model.Clusters[secondNearestClusterIndex];
double nearestClusterMeanDistance = 0.0;
double secondNearestClusterMeanDistance = 0.0;
foreach (Song song in nearestCluster)
{
double distance = model.DistanceFunc.GetDistance(song, analyzedSong.AssociatedSong);
nearestClusterMeanDistance += distance;
}
foreach (Song song in secondNearestCluster)
{
double distance = model.DistanceFunc.GetDistance(song, analyzedSong.AssociatedSong);
secondNearestClusterMeanDistance += distance;
}
nearestClusterMeanDistance /= nearestCluster.Count;
secondNearestClusterMeanDistance /= secondNearestCluster.Count;
double silhouetteCoef =
(secondNearestClusterMeanDistance - nearestClusterMeanDistance) /
Math.Max(nearestClusterMeanDistance, secondNearestClusterMeanDistance);
analyzedSong.SilhouetteCoef = silhouetteCoef;
silhouetteCoefMean += silhouetteCoef;
}
silhouetteCoefMean /= analyzedSongs.Count;
return(silhouetteCoefMean);
}
static void ShowSongsByClusters(BaseKMeans clusterizer)
{
Console.WriteLine();
Console.WriteLine($"Clusters size:");
clusterizer.Clusters.ForEach(cluster => Console.WriteLine($"Size: {cluster.Count}"));
}
public ModelAnalyzer(BaseKMeans model)
{
Model = model;
}
public SongSuccessPredictor(BaseKMeans clusterizer, IDistanceFunc distanceFunc)
{
Clusterizer = clusterizer;
DistanceFunc = distanceFunc;
Probabilities = new List <double>(Clusterizer.Clusters.Capacity);
}
