public void Training()
{
foreach (var data in Datas)
{
Distance = Math.Abs(data.Value - Clusters.ElementAt(0));
BeLong = new BeLongTo()
{
Cluster = 0,
Distance = Distance
};
for (var index = 0; index < Clusters.Count; index++)
{
Distance = Math.Abs(data.Value - Clusters[index]);
if (Distance <= BeLong.Distance)
{
BeLong.Cluster = index;
BeLong.Distance = Distance;
}
}
TrainingDatas[BeLong.Cluster].Data.Add(data);
}
}
public KMean(List <Data> datas, int sumCluster, int maxTraining = 1200)
{
Clusters = new List <double>();
Datas = new List <Data>(datas);
PreClusters = new List <double>();
TrainingDatas = new List <TrainingData>();
BeLong = new BeLongTo();
SumOfClusters = sumCluster;
MaxTrainingTimes = maxTraining;
}