protected override int Test(FeatureVector vector, out double[] details)
{
double[] votes_c = new double[NoOfClasses];
var nearestNeighbors = new List <IdValuePair <double> >();
for (int v_i = 0; v_i < TrainingVectors.Count; v_i++)
{
double distance = distanceFunc(TrainingVectors[v_i], vector);
// If this neighbor is closer than our furthest neighbor, ...
// If the list of nearest neighbors is empty OR this is the closest distance we'Ve seen,
// then add neighbor as the closest neighbor (i.e. insert at position 0).
if (nearestNeighbors.Count == 0 || distance < nearestNeighbors[0].Value)
{
nearestNeighbors.Insert(0, new IdValuePair <double>(v_i, distance));
votes_c[TrainingVectors[v_i].Headers[Gold_i]]++;
// If we have too many neighbors, then remove the furthest one.
if (nearestNeighbors.Count > K)
{
votes_c[TrainingVectors[nearestNeighbors[nearestNeighbors.Count - 1].Id].Headers[Gold_i]]--;
nearestNeighbors.RemoveAt(nearestNeighbors.Count - 1);
}
}
else if (nearestNeighbors.Count < K || distance < nearestNeighbors[nearestNeighbors.Count - 1].Value)
{
var newNeighbor = new IdValuePair <double>(v_i, distance);
int insert_b = SearchHelper.FindInsertIndex(nearestNeighbors, newNeighbor);
if (insert_b <= K)
{
nearestNeighbors.Insert(insert_b, newNeighbor);
votes_c[TrainingVectors[v_i].Headers[Gold_i]]++;
}
// If we have too many neighbors, then remove the furthest one.
if (nearestNeighbors.Count > K)
{
votes_c[TrainingVectors[nearestNeighbors[nearestNeighbors.Count - 1].Id].Headers[Gold_i]]--;
nearestNeighbors.RemoveAt(nearestNeighbors.Count - 1);
}
}
Debug.Assert(nearestNeighbors.Count <= K);
}
if (nearestNeighbors.Count < K)
{
Console.Error.WriteLine("Warning: K nearest neighbors could not be found.");
}
details = NormalizationHelper.CreateNormalizedDistribution(votes_c);
return(StatisticsHelper.ArgMax(votes_c));
}
public int CompareTo(IdValuePair <T> that)
{
return(Value.CompareTo(that.Value));
}
// Methods
public int CompareTo(object obj)
{
IdValuePair <T> that = (IdValuePair <T>)obj;
return(CompareTo(that));
}
