public virtual HashBag <int> getVotesBag(Neighbor[] kNN, int k, int[] unknown, IList <int> Y)
{
HashBag <int> votes = new HashBag <int>();
for (int i = 0; i < k && i < kNN.Length; i++)
{
votes.add(Y[kNN[i].corpusVectorIndex]);
}
if (dumpVotes && kNN.Length > 0)
{
Console.Write(Trainer.featureNameHeader(FEATURES));
InputDocument firstDoc = corpus.documentsPerExemplar[kNN[0].corpusVectorIndex]; // pick any neighbor to get parser
Console.WriteLine(Trainer._toString(FEATURES, firstDoc, unknown) + "->" + votes);
int size = Math.Min(k, kNN.Length);
kNN = kNN.Take(Math.Min(k, kNN.Length)).ToArray();
StringBuilder buf = new StringBuilder();
foreach (Neighbor n in kNN)
{
buf.Append(n.ToString(FEATURES, Y));
buf.Append("\n");
}
Console.WriteLine(buf);
}
return(votes);
}
public static HashBag <int> getCategoriesBag(ICollection <int> categories)
{
HashBag <int> votes = new HashBag <int>();
foreach (int category in categories)
{
votes.add(category);
}
return(votes);
}
