public string Classify(T NewNods)
{
List <KeyValuePair <T, float> > TrainedResultDistancePair = new List <KeyValuePair <T, float> >();
foreach (T Center in TrainedResult)
{
float DistanceGet = Center.GetEuclideanDistance(NewNods);
TrainedResultDistancePair.Add(new KeyValuePair <T, float>(Center, DistanceGet));
}
var ShortestGroup = TrainedResultDistancePair.OrderBy(x => x.Value).Select(x => x.Key);
var ShortestGroupTag = ShortestGroup.First().Tag;
OnClassify?.Invoke(NewNods, ShortestGroup, ShortestGroupTag);
NewNods.Tag = ShortestGroupTag;
return(ShortestGroupTag);
}
public KnnClassifyResult Classify(int k, T NewNode)
{
List <KeyValuePair <T, float> > NodeDistance = new List <KeyValuePair <T, float> >();
foreach (var ClassifiedNode in ClassifiedNodes)
{
var distance = ClassifiedNode.GetEuclideanDistance(NewNode);
if (Threshold != null && distance < Threshold)
{
NodeDistance.Add(new KeyValuePair <T, float>(ClassifiedNode, distance));
}
else
{
NodeDistance.Add(new KeyValuePair <T, float>(ClassifiedNode, distance));
}
}
var ClosestKPoints = NodeDistance.OrderBy(x => x.Value).Take(k);
var MostElementsGroup = ClosestKPoints
.GroupBy(node => node.Key.Tag)
.OrderByDescending(group => group.Count())
.First();
float confidence = ((float)MostElementsGroup.Count()) / ((float)k);
string MostTag = MostElementsGroup.Key;
NewNode.Tag = MostTag;
OnClassify?.Invoke(NewNode, ClosestKPoints.Select(x => x.Key), MostTag, ClassifiedNodes);
return(new KnnClassifyResult()
{
Tag = MostTag, Confidence = confidence
});
}