public static Dictionary <string, int> Cluster(IEnumerable <string> itemIds, double[,] features, int numClusters, string centerPath = "",
ClusteringAlgorithm algorithm = ClusteringAlgorithm.KMeans)
{
Console.WriteLine("Clustering...");
//features = Normalized(features);
Console.WriteLine("Features normalized.");
var dm = new DoubleMatrix(features);
ClusterSet clusters = null;
if (algorithm == ClusteringAlgorithm.KMeans)
{
var km = new KMeansClustering(dm);
km.Cluster(numClusters);
Console.WriteLine("Num Clusters: {0}, Num Items: {1}, Num Iterations: {2}", km.K, km.N, km.Iterations);
if (centerPath != "")
{
var cWriter = new StreamWriter(centerPath);
km.FinalCenters.WriteAsCSV(cWriter);
cWriter.Close();
}
clusters = km.Clusters;
}
else
{
var nmf = new NMFClustering <NMFDivergenceUpdate>();
nmf.Factor(dm, numClusters);
if (nmf.Converged)
{
var uWriter = new StreamWriter(Paths.AmazonBooksUsersCluster + ".nmf");
var iWriter = new StreamWriter(Paths.AmazonBooksItemsCluster + ".nmf");
nmf.W.WriteAsCSV(uWriter);
nmf.H.WriteAsCSV(iWriter);
uWriter.Flush();
iWriter.Flush();
uWriter.Close();
iWriter.Close();
File.WriteAllLines(Paths.AmazonBooksUsersCluster + ".con", nmf.Connectivity.ToTabDelimited().Split('\n'));
clusters = nmf.ClusterSet;
File.WriteAllLines(Paths.AmazonBooksUsersCluster + ".cluster", clusters.Clusters.Select(c => c.ToString()));
Console.WriteLine("Successfully wrote decompose matrixes.");
}
else
{
Console.WriteLine("Factorization failed to converge in {0} iterations.", nmf.MaxFactorizationIterations);
}
}
return(itemIds.Zip(clusters.Clusters, (i, c) => new { ItemId = i, Cluster = c }).ToDictionary(i => i.ItemId, i => i.Cluster));
}
public static Dictionary<string, int> Cluster(IEnumerable<string> itemIds, double[,] features, int numClusters, string centerPath = "",
ClusteringAlgorithm algorithm = ClusteringAlgorithm.KMeans)
{
Console.WriteLine("Clustering...");
//features = Normalized(features);
Console.WriteLine("Features normalized.");
var dm = new DoubleMatrix(features);
ClusterSet clusters = null;
if (algorithm == ClusteringAlgorithm.KMeans)
{
var km = new KMeansClustering(dm);
km.Cluster(numClusters);
Console.WriteLine("Num Clusters: {0}, Num Items: {1}, Num Iterations: {2}", km.K, km.N, km.Iterations);
if (centerPath != "")
{
var cWriter = new StreamWriter(centerPath);
km.FinalCenters.WriteAsCSV(cWriter);
cWriter.Close();
}
clusters = km.Clusters;
}
else
{
var nmf = new NMFClustering<NMFDivergenceUpdate>();
nmf.Factor(dm, numClusters);
if (nmf.Converged)
{
var uWriter = new StreamWriter(Paths.AmazonBooksUsersCluster + ".nmf");
var iWriter = new StreamWriter(Paths.AmazonBooksItemsCluster + ".nmf");
nmf.W.WriteAsCSV(uWriter);
nmf.H.WriteAsCSV(iWriter);
uWriter.Flush();
iWriter.Flush();
uWriter.Close();
iWriter.Close();
File.WriteAllLines(Paths.AmazonBooksUsersCluster + ".con", nmf.Connectivity.ToTabDelimited().Split('\n'));
clusters = nmf.ClusterSet;
File.WriteAllLines(Paths.AmazonBooksUsersCluster + ".cluster", clusters.Clusters.Select(c => c.ToString()));
Console.WriteLine("Successfully wrote decompose matrixes.");
}
else
{
Console.WriteLine("Factorization failed to converge in {0} iterations.", nmf.MaxFactorizationIterations);
}
}
return itemIds.Zip(clusters.Clusters, (i, c) => new { ItemId = i, Cluster = c }).ToDictionary(i => i.ItemId, i => i.Cluster);
}
