コード例 #1
0
 public double EuclideanDistance(DataItem data, DataItem mean)
 {
     double difference = 0;
     difference = Math.Pow(data.X - mean.X, 2);
     difference += Math.Pow(data.Y - mean.Y, 2);
     return Math.Sqrt(difference);
 }
コード例 #2
0
ファイル: DBSCAN.cs プロジェクト: superviktor/Kmeans
 static bool ExpandCluster(List<DataItem> points, DataItem p, int clusterId, double eps, int minPts)
 {
     List<DataItem> seeds = GetRegion(points, p, eps);
     if (seeds.Count < minPts) // no core point
     {
         p.Cluster = Point.NOISE;
         return false;
     }
     else // all points in seeds are density reachable from point 'p'
     {
         for (int i = 0; i < seeds.Count; i++) seeds[i].Cluster = clusterId;
         seeds.Remove(p);
         while (seeds.Count > 0)
         {
             DataItem currentP = seeds[0];
             List<DataItem> result = GetRegion(points, currentP, eps);
             if (result.Count >= minPts)
             {
                 for (int i = 0; i < result.Count; i++)
                 {
                     DataItem resultP = result[i];
                     if (resultP.Cluster == DataItem.UNCLASSIFIED || resultP.Cluster == DataItem.NOISE)
                     {
                         if (resultP.Cluster == Point.UNCLASSIFIED) seeds.Add(resultP);
                         resultP.Cluster = clusterId;
                     }
                 }
             }
             seeds.Remove(currentP);
         }
         return true;
     }
 }
コード例 #3
0
ファイル: Forel.cs プロジェクト: superviktor/Kmeans
        public void Cluster()
        {
            while (points.Count > 0)
            {

                Random rnd = new Random();
                var index = rnd.Next(0, points.Count);
                DataItem center = points[index];
                DataItem newCenter = center;
                //inside points
                List<DataItem> lst = new List<DataItem>();
                while (center == newCenter)
                {
                    foreach (var p in points)
                    {
                        if (Math.Sqrt(Math.Pow((p.X - center.X), 2) + Math.Pow((p.Y - center.Y), 2)) < R)
                        {
                            lst.Add(p);
                        }
                    }
                    //power center
                    double powerX = 0;
                    double powerY = 0;
                    foreach (var p in lst)
                    {
                        powerX += p.X;
                        powerY += p.Y;
                    }
                    double powerCenterX = powerX / lst.Count;
                    double powerCenterY = powerY / lst.Count;
                    newCenter = new DataItem(powerCenterX, powerCenterY);
                }
                result.Add(lst);
                centers.Add(newCenter);
                foreach (var p in lst)
                {
                    points.Remove(p);
                }
            }
        }
コード例 #4
0
ファイル: DBSCAN.cs プロジェクト: superviktor/Kmeans
 static List<DataItem> GetRegion(List<DataItem> points, DataItem p, double eps)
 {
     List<DataItem> region = new List<DataItem>();
     for (int i = 0; i < points.Count; i++)
     {
         int distSquared = DataItem.DistanceSquared(p, points[i]);
         if (distSquared <= eps) region.Add(points[i]);
     }
     return region;
 }
コード例 #5
0
ファイル: DataItem.cs プロジェクト: superviktor/Kmeans
 public static int DistanceSquared(DataItem p1, DataItem p2)
 {
     double diffX = p2.X - p1.X;
     double diffY = p2.Y - p1.Y;
     return (int) (diffX * diffX + diffY * diffY);
 }