C#或vb.net中的DBSCAN代码,用于Cluster Analysis

using System;
using System.Collections.Generic;
using System.Linq;

public class DBSCAN
{
    private double eps;
    private int minPts;
    private List<double[]> dataset;

    public DBSCAN(double eps, int minPts, List<double[]> dataset)
    {
        this.eps = eps;
        this.minPts = minPts;
        this.dataset = dataset;
    }

    public List<int> Run()
    {
        int n = dataset.Count;
        bool[] visited = new bool[n];
        List<int> cluster = new List<int>();
        for (int i = 0; i < n; i++)
        {
            if (!visited[i])
            {
                List<int> neighbors = RegionQuery(i);
                if (neighbors.Count < minPts)
                {
                    visited[i] = true;
                }
                else
                {
                    cluster.Add(ExpandCluster(i, neighbors));
                }
            }
        }
        return cluster;
    }

    private List<int> RegionQuery(int i)
    {
        List<int> neighbors = new List<int>();
        for (int j = 0; j< dataset.Count; j++)
        {
            if (i != j && Distance(dataset[i], dataset[j]) <= eps)
            {
                neighbors.Add(j);
            }
        }
        return neighbors;
    }

    private int ExpandCluster(int i, List<int> neighbors)
    {
        int clusterId = i;
        visited[i] = true;
        List<int> seeds = new List<int>(neighbors);
        while (seeds.Count > 0)
        {
            int current = seeds[0];
            seeds.RemoveAt(0);
            List<int> currentNeighbors = RegionQuery(current);
            if (currentNeighbors.Count >= minPts)
            {
                foreach (int neighbor in currentNeighbors)
                {
                    if (!visited[neighbor])
                    {
                        seeds.Add(neighbor);
                    }
                }
            }
            if (!visited[current])
            {
                visited[current] = true;
                clusterId = current;
            }
        }
        return clusterId;
    }

    private double Distance(double[] a, double[] b)
    {
        double sum = 0;
        for (int i = 0; i < a.Length; i++)
        {
            sum += Math.Pow(a[i] - b[i], 2);
        }
        return Math.Sqrt(sum);
    }
}

List<double[]> dataset = new List<double[]>
{
    new double[] { 1, 2 },
    new double[] { 2, 3 },
    new double[] { 3, 4 },
    new double[] { 8, 7 },
    new double[] { 8, 8 },
    new double[] { 9, 8 },
    new double[] { 10, 10 },
    new double[] { 12, 11 },
    new double[] { 12, 12 },
    new double[] { 13, 12 }
};

DBSCAN dbscan = new DBSCAN(eps: 1.5, minPts: 3, dataset: dataset);
List<int> clusters = dbscan.Run();
Console.WriteLine(string.Join(", ", clusters));