无法获得模糊 C 意味着工作

Question

我需要找出为什么质心位置如此接近？

我在这里 http://msugvnua000.web710.discountasp.net/Posts/Details/3347 发现了一些模糊的 c 表示代码，并非常努力地将其转换为 java 代码（如下），但我缺少一些东西。

我还尝试查看此实现http://www.codeproject.com/Articles/91675/Computer-Vision-Applications-with-C-Fuzzy-C-means 代码看起来很相似，但它不同，因为不是更新集群索引而是更新成员值 - 我不确定为什么要实现此更改？

public class CMeansAlgorithm3 {
    private static int fuzzyness = 2;

    private final Map<Double, Species> integerClusterHashMap = new HashMap<Double, Species>();

    /// Array containing all points used by the algorithm
    private List<Job> points;

    /// Gets or sets membership matrix
    public double[][] U;

    /// Algorithm precision
    private double eps = Math.pow(10, -5);

    /// Gets or sets objective function
    private double J;

    /// Gets or sets log message
    public String log;

    private List<Species> clusterList;

    public CMeansAlgorithm3(List<Job> points, int clusterSize){
        this.points = points;
        clusterList = initialiseCentroids(points, clusterSize);
        U = new double[points.size()][clusterList.size()];
        calculateClusterMembershipValues();
        recalculateClusterIndexes();
    }

    private void calculateClusterMembershipValues() {
        // Iterate through all points to create initial U matrix
        for (int i = 0; i < points.size(); i++) {
            Job p = points.get(i);
            double sum = 0.0;

            for (int j = 0; j < clusterList.size(); j++) {
                Cluster c = clusterList.get(j);
                double diff = Math.sqrt(Math.pow(p.getMidpointX() - c.getCentroid().getX(), 2.0) + Math.pow(p.getMidpointY() - c.getCentroid().getY(), 2.0));
                U[i][j] = (diff == 0) ? eps : diff;
                sum += U[i][j];
             }

             double sum2 = 0.0;
             for (int j = 0; j < clusterList.size(); j++) {
                 U[i][j] = 1.0 / Math.pow(U[i][j] / sum, 2.0 / (fuzzyness - 1.0));
                sum2 += U[i][j];
             }

             for (int j = 0; j < clusterList.size(); j++) {
                U[i][j] = U[i][j] / sum2;
             }    
        }
   }

   /// Recalculates cluster indexes
   private void recalculateClusterIndexes() {
        for (int i = 0; i < points.size(); i++) {
            double max = -1.0;
            Job p = points.get(i);

            for (int j = 0; j < clusterList.size(); j++) {
                max = U[i][j] > max ? U[i][j] : max;
//              if (max < U[i][j]) {
//                    max = U[i][j];
//                    p.setClusterIndex((max == 0.5) ? 0.5 : j);
//              }
            }
            p.setClusterIndex(max);
        }
    }

    /// Perform a complete run of the algorithm until the desired accuracy is achieved.
    /// For demonstration issues, the maximum Iteration counter is set to 20.
    /// Algorithm accuracy
    /// The number of steps the algorithm needed to complete
    public List<Species> run(double accuracy) {
        int k = 0;
        int maxIterations = 100;

        do {
            k++;
            J = calculateObjectiveFunction();
            calculateClusterCentroids();
            step();
            double Jnew = calculateObjectiveFunction();

            if (Math.abs(J - Jnew) < accuracy) break;
        }
        while (maxIterations > k);

        assignJobsToClusters();
        return clusterList;
    }

    /// Calculate the objective function
    /// The objective function as double value
    private double calculateObjectiveFunction() {
        double Jk = 0;

        for (int i = 0; i < this.points.size();i++) {
            for (int j = 0; j < clusterList.size(); j++) {
                Jk += Math.pow(U[i][j], this.fuzzyness) * Math.pow(this.calculateEuclidDistance(points.get(i), clusterList.get(j)), 2);
            }
        }
        return Jk;
    }

    private List<Species> initialiseCentroids(final List<Job> dataSet, final int speciesSize) {
        final List<Species> clusterList = new ArrayList<Species>();
        final List<Integer> uniqueIndexes = ToolBox.uniqueIndexes(dataSet.size(), speciesSize);

        for (int i=0; i< uniqueIndexes.size(); i++){
            final int randomIndex = uniqueIndexes.get(i);
            final Species species = new Species(i);
            final Centroid centroid = new Centroid(dataSet.get(randomIndex).getMidpointX(), dataSet.get(randomIndex).getMidpointY(), i);
            species.setCentroid(centroid);
            speciesList.add(species);
        }
        return clusterList;
    }

    /// Perform one step of the algorithm
    public void step() {
        for (int c = 0; c < clusterList.size(); c++) {
            for (int h = 0; h < points.size(); h++) {
                double top;
                top = calculateEuclidDistance(points.get(h), clusterList.get(c));
                if (top < 1.0) top = eps;

                // sumTerms is the sum of distances from this data point to all clusters.
                double sumTerms = 0.0;

                for (int ck = 0; ck < clusterList.size(); ck++) {
                    double thisDistance = calculateEuclidDistance(points.get(h), clusterList.get(ck));
                    if (thisDistance < 1.0) thisDistance = eps;
                    sumTerms += Math.pow(top / thisDistance, 2.0 / (fuzzyness - 1.0));

                }
                // Then the membership value can be calculated as...
                U[h][c] = (1.0 / sumTerms);
            }
        }

        recalculateClusterIndexes();
    }

    /// Calculates Euclid distance between point and centroid
    /// Point
    /// Centroid
    /// Calculated distance
    private double calculateEuclidDistance(Job p, Species c) {
        return ToolBox.calculateDistance(p.getMidpointX(), p.getMidpointY(), c.getCentroid().getX(), c.getCentroid().getY());
    }

    /// Calculates the centroids of the clusters
    private void calculateClusterCentroids() {
        for (int j = 0; j < clusterList.size(); j++) {
            Species c = clusterList.get(j);
            double uX = 0.0;
            double uY = 0.0;
            double membershipSum = 0.0;

            for (int i = 0; i < points.size(); i++) {
                Job p = points.get(i);

                double uu = Math.pow(U[i][j], this.fuzzyness);
                uX += uu * p.getMidpointX();
                uY += uu * p.getMidpointY();
                membershipSum += uu;
            }

            c.setMembershipSum(membershipSum);
            c.getCentroid().setX(((uX / membershipSum)));
            c.getCentroid().setY(((uY / membershipSum)));

            log += String.format("Cluster Centroid: (" + c.getCentroid().getX() + "; " + c.getCentroid().getY() + ")");
        }
    }

    private void assignJobsToClusters(){
        for (final Cluster cluster : clusterList){
            if (!integerClusterHashMap.containsKey(cluster.getMembershipSum()))
                integerClusterHashMap.put(cluster.getMembershipSum(), cluster);
        }

        for (Job job : points){
            final double clusterIndex = job.getClusterIndex();
            Species c = integerSpeciesHashMap.get(clusterIndex);

            if (c != null) {
                c.add(job);
            }
        }
    }

Answer 1

fuzzy c 表示java中的代码

package f;
import java.io.File;
import java.io.FileNotFoundException;
import java.util.Scanner;

/**
 *
 * @author Anooj.k.varghese
 */
public class F{

 static Double data_set[][]=new Double[20000][100];
    static Double diff[][]=new Double[20000][100];
        static Double eud[][]=new Double[20000][1000];
    static Double intial_centroid[][]=new Double[300][400];
     static Double new_center[][]=new Double[300][400];
    static int num = 0;
    static int row=4;//rows in Your DataSet here i use iris dataset 

    static int cnum;
    static int itc=0;
    static int checker=1;


     private static void readFile() throws FileNotFoundException
        {
        Scanner scanner = new Scanner(new File("E:/aa.txt"));//Dataset path
        scanner.useDelimiter(System.getProperty("line.separator"));
        //scanner.useDelimiter(",");
        int lineNo = 0;
            while (scanner.hasNext())
             {
                parseLine(scanner.next(),lineNo);
                lineNo++;
                System.out.println();
             }
             // System.out.println("total"+num); PRINT THE TOTAL
     scanner.close();
        }
    //read file is copey to the data_set
    public static void parseLine(String line,int lineNo)
      { itc=0;
        Scanner lineScanner = new Scanner(line);
        lineScanner.useDelimiter(",");
          for(int col=0;col<row;col++)
              {
                  Double arry=lineScanner.nextDouble();
                  data_set[num][col]=arry;                          ///here read  data set is assign the variable data_set
               }
         num++;

        }
    public static void init()
    {
        for(int i=0;i<num;i++)
        { 
         data_set[i][row]=0.0;
         data_set[i][row+1]=0.0;
        }
    }
    public static void print()
    {
        double re=0;
        double a=0;


       if(itc==0)
       {

             System.out.println("ENTER K");
         Scanner sc=new Scanner(System.in);      
         cnum=sc.nextInt();   //enter the number of cenroid
       System.out.println("centroid");
         for(int i=0;i<cnum;i++)
         {
            for(int j=0;j<row;j++)
                {

                    intial_centroid[i][j]=data_set[i][j];                  //// CENTROID ARE STORED IN AN intial_centroid variable
                    System.out.print(intial_centroid[i][j]);      
                }
            System.out.println();
         }

       }
       else
       {

            for(int i=0;i<cnum;i++)
         {
            for(int j=0;j<row;j++)
                {
                    intial_centroid[i][j]=new_center[i][j];                  //// CENTROID ARE STORED IN AN intial_centroid variable
                    System.out.print(intial_centroid[i][j]);      
                }
            System.out.println();
         }


       }

          for(int i=0;i<num;i++)
        {
                for(int j=0;j<cnum;j++)       
                {
                    re=0;
                     for(int k=0;k<row;k++)
                     {
                            a= (intial_centroid[j][k]-data_set[i][k]);
                            //System.out.println(a);
                             a=a*a;
                             re=re+a;                                                 // store the row sum

                        }

                         diff[i][j]= Math.sqrt(re);// find the squre root
                         System.out.println(diff[i][j]);

        }
        }

    }
    public static void s()
    {

        double b,c;
        for(int i=0;i<num;i++)
        {
            for(int j=0;j<cnum;j++)
            {
                c=0.0;
                b=0.0;
                for(int k=0;k<cnum;k++)
                {
                    if(diff[i][k]==0)
                   {
                        b=0;
                    }
                 if(diff[i][k]!=0)
                   {
                    b=diff[i][j]/diff[i][k];
                    }
                    c=c+b;
                }
                if(c==0)
                {
                    eud[i][j]=0.0;
                }
                else
                {
                     eud[i][j]=1/c;
                }
            }


        }
        double a=0;
          for(int i=0;i<num;i++)
        {
            a=0;
            for(int j=0;j<cnum;j++)
            {
                a=a+eud[i][j];
             System.out.print(eud[i][j]+"    ");
            }
            System.out.print("total  "+a);
            System.out.println();
            }
          double aaa;
          int counter=0;
               for(int i=0;i<num;i++)
        {counter=0;
            aaa=eud[i][0];
            for(int j=0;j<cnum;j++)
                        {
                            if(aaa<=eud[i][j])
                            {
                                aaa=eud[i][j];
                                counter=j;
                            }
                        }
          if(itc%2==0)
          {
                data_set[i][row]=(double)counter;
          }

           if(itc%2==1)
          {
               data_set[i][row+1]=(double)counter;
          }
        }
           for(int i=0;i<num;i++)
           {
               for(int j=0;j<=row+1;j++)
               {
                System.out.print(data_set[i][j]+",  ");

               }
               System.out.println();
           }
    }

     public static void newcenter()
          {
              itc++;
              double a=0.0;
              double c=0.0;
              double d=0.0;
              double f=0.0;
              for(int k=0;k<cnum;k++)
              {
                   for(int j=0;j<row;j++)
                  {
                      a=0.0;
                      d=0.0;

                 c=0.0;
                 f=0.0;
                      for(int i=0;i<num;i++)
                      {
                          //System.out.print("edu"+eud[i][k]);
                          a=eud[i][k];
                          a=a*a;
                          c=c+a;
                          //System.out.println("data"+data_set[i][j]);
                          d=a*data_set[i][j];
                          f=f+d;
                      }
                      new_center[k][j]=f/c;
                         System.out.println("centroid new "+new_center[k][j]);
                     // j=row+5;
                    //  k=cnum+5;

                  }
              }
          }


     public static void print11()
    {
        System.out.println();
         System.out.println();
          System.out.println();
        System.out.println("----OUTPUT----");
        int c=0;
        int a=0;
        for(int i=0;i<cnum;i++)
        {
            System.out.println("---------CLUSTER-"+i+"-----");
         a=0;
            for(int j=0;j<num;j++)
            {
                 if(data_set[j][row]==i)
                 {a++;
                for(int k=0;k<row;k++)
                {

                    System.out.print(data_set[j][k]+"  ");
                }
                c++;
                System.out.println();
                }
                 //System.out.println(num);

            }
               System.out.println("CLUSTER INSTANCES="+a);


        }
        System.out.println("TOTAL INSTANCE"+c);
    }


    public static void check()
{

    checker=0;
    for(int i=0;i<num;i++)
    {
         //System.out.println("hii");
        if(Double.compare(data_set[i][row],data_set[i][row+1]) != 0)

        {
            checker=1;
            //System.out.println("hii " + i  + " " + data_set[i][4]+ " "+data_set[i][4]);
            break;
        }
        System.out.println();
    }

}

    public static void main(String[] args) throws FileNotFoundException {
  readFile();
   //
  init();
while(checker!=0)
 //for(int i=0;i<5;i++) 
  {

  print();
 s();
 newcenter();
 check();

    }
print11();
}
}