├── .classpath
├── .gitignore
├── .project
├── .settings
    └── org.eclipse.jdt.core.prefs
├── README.md
└── src
    ├── Jama
        └── examples
        │   ├── MagicSquareExample.java
        │   └── SVD.java
    └── com
        └── pku
            └── yangliu
                ├── ClusterMain.java
                ├── ComputeWordsVector.java
                ├── DataPreProcess.java
                ├── DimensionReduction.java
                ├── KmeansCluster.java
                ├── KmeansSVDCluster.java
                └── PorterAlgorithm.java


/.classpath:
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1 | <?xml version="1.0" encoding="UTF-8"?>
2 | <classpath>
3 | 	<classpathentry kind="src" path="src"/>
4 | 	<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/JavaSE-1.6"/>
5 | 	<classpathentry kind="lib" path="Jama-1.0.2.jar"/>
6 | 	<classpathentry kind="output" path="bin"/>
7 | </classpath>
8 | 


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/.gitignore:
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1 | *.class
2 | 
3 | # Package Files #
4 | *.jar
5 | *.war
6 | *.ear
7 | 


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/.project:
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 1 | <?xml version="1.0" encoding="UTF-8"?>
 2 | <projectDescription>
 3 | 	<name>DataMiningCluster</name>
 4 | 	<comment></comment>
 5 | 	<projects>
 6 | 	</projects>
 7 | 	<buildSpec>
 8 | 		<buildCommand>
 9 | 			<name>org.eclipse.jdt.core.javabuilder</name>
10 | 			<arguments>
11 | 			</arguments>
12 | 		</buildCommand>
13 | 	</buildSpec>
14 | 	<natures>
15 | 		<nature>org.eclipse.jdt.core.javanature</nature>
16 | 	</natures>
17 | </projectDescription>
18 | 


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/.settings/org.eclipse.jdt.core.prefs:
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 1 | #Tue Mar 20 12:44:23 CST 2012
 2 | eclipse.preferences.version=1
 3 | org.eclipse.jdt.core.compiler.codegen.inlineJsrBytecode=enabled
 4 | org.eclipse.jdt.core.compiler.codegen.targetPlatform=1.6
 5 | org.eclipse.jdt.core.compiler.codegen.unusedLocal=preserve
 6 | org.eclipse.jdt.core.compiler.compliance=1.6
 7 | org.eclipse.jdt.core.compiler.debug.lineNumber=generate
 8 | org.eclipse.jdt.core.compiler.debug.localVariable=generate
 9 | org.eclipse.jdt.core.compiler.debug.sourceFile=generate
10 | org.eclipse.jdt.core.compiler.problem.assertIdentifier=error
11 | org.eclipse.jdt.core.compiler.problem.enumIdentifier=error
12 | org.eclipse.jdt.core.compiler.source=1.6
13 | 


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/README.md:
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 1 | DataMiningCluster
 2 | =================
 3 | 
 4 | Implementation of text clustering algorithms including K-means, MBSAS, DBSCAN.
 5 | 
 6 | Author: Liu Yang(yangliuyx@gmail.com)
 7 | 
 8 | Author's blog: http://blog.csdn.net/yangliuy
 9 | 
10 | A Chinese technical blog related to this code package: http://blog.csdn.net/yangliuy/article/details/7471659
11 | 


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/src/Jama/examples/MagicSquareExample.java:
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  1 | package Jama.examples;
  2 | import Jama.*; 
  3 | import java.util.Date;
  4 | 
  5 | /** Example of use of Matrix Class, featuring magic squares. **/
  6 | 
  7 | public class MagicSquareExample {
  8 | 
  9 |    /** Generate magic square test matrix. **/
 10 | 
 11 |    public static Matrix magic (int n) {
 12 | 
 13 |       double[][] M = new double[n][n];
 14 | 
 15 |       // Odd order
 16 | 
 17 |       if ((n % 2) == 1) {
 18 |          int a = (n+1)/2;
 19 |          int b = (n+1);
 20 |          for (int j = 0; j < n; j++) {
 21 |             for (int i = 0; i < n; i++) {
 22 |                M[i][j] = n*((i+j+a) % n) + ((i+2*j+b) % n) + 1;
 23 |             }
 24 |          }
 25 | 
 26 |       // Doubly Even Order
 27 | 
 28 |       } else if ((n % 4) == 0) {
 29 |          for (int j = 0; j < n; j++) {
 30 |             for (int i = 0; i < n; i++) {
 31 |                if (((i+1)/2)%2 == ((j+1)/2)%2) {
 32 |                   M[i][j] = n*n-n*i-j;
 33 |                } else {
 34 |                   M[i][j] = n*i+j+1;
 35 |                }
 36 |             }
 37 |          }
 38 | 
 39 |       // Singly Even Order
 40 | 
 41 |       } else {
 42 |          int p = n/2;
 43 |          int k = (n-2)/4;
 44 |          Matrix A = magic(p);
 45 |          for (int j = 0; j < p; j++) {
 46 |             for (int i = 0; i < p; i++) {
 47 |                double aij = A.get(i,j);
 48 |                M[i][j] = aij;
 49 |                M[i][j+p] = aij + 2*p*p;
 50 |                M[i+p][j] = aij + 3*p*p;
 51 |                M[i+p][j+p] = aij + p*p;
 52 |             }
 53 |          }
 54 |          for (int i = 0; i < p; i++) {
 55 |             for (int j = 0; j < k; j++) {
 56 |                double t = M[i][j]; M[i][j] = M[i+p][j]; M[i+p][j] = t;
 57 |             }
 58 |             for (int j = n-k+1; j < n; j++) {
 59 |                double t = M[i][j]; M[i][j] = M[i+p][j]; M[i+p][j] = t;
 60 |             }
 61 |          }
 62 |          double t = M[k][0]; M[k][0] = M[k+p][0]; M[k+p][0] = t;
 63 |          t = M[k][k]; M[k][k] = M[k+p][k]; M[k+p][k] = t;
 64 |       }
 65 |       return new Matrix(M);
 66 |    }
 67 | 
 68 |    /** Shorten spelling of print. **/
 69 | 
 70 |    private static void print (String s) {
 71 |       System.out.print(s);
 72 |    }
 73 |    
 74 |    /** Format double with Fw.d. **/
 75 | 
 76 |    public static String fixedWidthDoubletoString (double x, int w, int d) {
 77 |       java.text.DecimalFormat fmt = new java.text.DecimalFormat();
 78 |       fmt.setMaximumFractionDigits(d);
 79 |       fmt.setMinimumFractionDigits(d);
 80 |       fmt.setGroupingUsed(false);
 81 |       String s = fmt.format(x);
 82 |       while (s.length() < w) {
 83 |          s = " " + s;
 84 |       }
 85 |       return s;
 86 |    }
 87 | 
 88 |    /** Format integer with Iw. **/
 89 | 
 90 |    public static String fixedWidthIntegertoString (int n, int w) {
 91 |       String s = Integer.toString(n);
 92 |       while (s.length() < w) {
 93 |          s = " " + s;
 94 |       }
 95 |       return s;
 96 |    }
 97 | 
 98 | 
 99 |    public static void main (String argv[]) {
100 | 
101 |    /* 
102 |     | Tests LU, QR, SVD and symmetric Eig decompositions.
103 |     |
104 |     |   n       = order of magic square.
105 |     |   trace   = diagonal sum, should be the magic sum, (n^3 + n)/2.
106 |     |   max_eig = maximum eigenvalue of (A + A')/2, should equal trace.
107 |     |   rank    = linear algebraic rank,
108 |     |             should equal n if n is odd, be less than n if n is even.
109 |     |   cond    = L_2 condition number, ratio of singular values.
110 |     |   lu_res  = test of LU factorization, norm1(L*U-A(p,:))/(n*eps).
111 |     |   qr_res  = test of QR factorization, norm1(Q*R-A)/(n*eps).
112 |     */
113 | 
114 |       print("\n    Test of Matrix Class, using magic squares.\n");
115 |       print("    See MagicSquareExample.main() for an explanation.\n");
116 |       print("\n      n     trace       max_eig   rank        cond      lu_res      qr_res\n\n");
117 |  
118 |       Date start_time = new Date();
119 |       double eps = Math.pow(2.0,-52.0);
120 |       for (int n = 3; n <= 32; n++) {
121 |          print(fixedWidthIntegertoString(n,7));
122 | 
123 |          Matrix M = magic(n);
124 | 
125 |          int t = (int) M.trace();
126 |          print(fixedWidthIntegertoString(t,10));
127 | 
128 |          EigenvalueDecomposition E =
129 |             new EigenvalueDecomposition(M.plus(M.transpose()).times(0.5));
130 |          double[] d = E.getRealEigenvalues();
131 |          print(fixedWidthDoubletoString(d[n-1],14,3));
132 | 
133 |          int r = M.rank();
134 |          print(fixedWidthIntegertoString(r,7));
135 | 
136 |          double c = M.cond();
137 |          print(c < 1/eps ? fixedWidthDoubletoString(c,12,3) :
138 |             "         Inf");
139 | 
140 |          LUDecomposition LU = new LUDecomposition(M);
141 |          Matrix L = LU.getL();
142 |          Matrix U = LU.getU();
143 |          int[] p = LU.getPivot();
144 |          Matrix R = L.times(U).minus(M.getMatrix(p,0,n-1));
145 |          double res = R.norm1()/(n*eps);
146 |          print(fixedWidthDoubletoString(res,12,3));
147 | 
148 |          QRDecomposition QR = new QRDecomposition(M);
149 |          Matrix Q = QR.getQ();
150 |          R = QR.getR();
151 |          R = Q.times(R).minus(M);
152 |          res = R.norm1()/(n*eps);
153 |          print(fixedWidthDoubletoString(res,12,3));
154 | 
155 |          print("\n");
156 |       }
157 |       Date stop_time = new Date();
158 |       double etime = (stop_time.getTime() - start_time.getTime())/1000.;
159 |       print("\nElapsed Time = " + 
160 |          fixedWidthDoubletoString(etime,12,3) + " seconds\n");
161 |       print("Adios\n");
162 |    }
163 | }
164 | 
165 | 


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/src/Jama/examples/SVD.java:
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 1 | package Jama.examples;
 2 | /*************************************************************************
 3 |  *  Compilation:  javac -classpath .:jama.jar SVD.java
 4 |  *  Execution:    java  -classpath .:jama.jar SVD
 5 |  *  Dependencies: jama.jar
 6 |  *  
 7 |  *  Test client for computing singular values of a matrix.
 8 |  *  
 9 |  *       http://math.nist.gov/javanumerics/jama/
10 |  *       http://math.nist.gov/javanumerics/jama/Jama-1.0.1.jar
11 |  *
12 |  *************************************************************************/
13 | 
14 | import Jama.Matrix;
15 | import Jama.SingularValueDecomposition;
16 | 
17 | public class SVD {
18 |    public static void main(String[] args) { 
19 | 
20 |       // create M-by-N matrix that doesn't have full rank
21 |       int M = 8, N = 5;
22 |       //Matrix B = Matrix.random(5, 3);
23 |       //Matrix A = Matrix.random(M, N).times(B).times(B.transpose());
24 |       double[][] vals = {{1, 1, 1, 0, 0},{2, 2, 2, 0, 0},{1, 1, 1, 0, 0},{5, 5, 5, 0, 0},{0, 0 ,0 , 2, 2},{0, 0 ,0 , 3, 3},{0, 0 ,0 , 1, 1}};
25 |       Matrix A = new Matrix(vals);
26 |       System.out.print("A = ");
27 |       A.print(9, 6);
28 | 
29 |       // compute the singular vallue decomposition
30 |       System.out.println("A = U S V^T");
31 |       System.out.println();
32 |       SingularValueDecomposition s = A.svd();
33 |       System.out.print("U = ");
34 |       Matrix U = s.getU();
35 |       U.print(9, 6);
36 |       System.out.print("Sigma = ");
37 |       Matrix S = s.getS();
38 |       S.print(9, 6);
39 |       System.out.print("V = ");
40 |       Matrix V = s.getV();
41 |       V.print(9, 6);
42 |       System.out.println("rank = " + s.rank());
43 |       System.out.println("condition number = " + s.cond());
44 |       System.out.println("2-norm = " + s.norm2());
45 | 
46 |       // print out singular values
47 |       System.out.print("singular values = ");
48 |       Matrix svalues = new Matrix(s.getSingularValues(), 1);
49 |       svalues.print(9, 6);
50 |       
51 |      // S.set(1, 1, 0);
52 |       //S.set(3, 3, 0);
53 |      // S.set(4, 4, 0);
54 |       System.out.print("Sigma = ");
55 |       S.print(9, 6);
56 |       Matrix B = U.times(S.times(V.transpose()));
57 |       System.out.print("B = ");
58 |       B.print(9, 6);
59 |    }
60 | 
61 | }
62 | 
63 | 


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/src/com/pku/yangliu/ClusterMain.java:
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https://raw.githubusercontent.com/yangliuy/DataMiningCluster/9676117108e44d348ce09356c42adfe4d3129deb/src/com/pku/yangliu/ClusterMain.java


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/src/com/pku/yangliu/ComputeWordsVector.java:
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/src/com/pku/yangliu/DataPreProcess.java:
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/src/com/pku/yangliu/DimensionReduction.java:
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/src/com/pku/yangliu/KmeansCluster.java:
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https://raw.githubusercontent.com/yangliuy/DataMiningCluster/9676117108e44d348ce09356c42adfe4d3129deb/src/com/pku/yangliu/KmeansCluster.java


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/src/com/pku/yangliu/KmeansSVDCluster.java:
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/src/com/pku/yangliu/PorterAlgorithm.java:
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https://raw.githubusercontent.com/yangliuy/DataMiningCluster/9676117108e44d348ce09356c42adfe4d3129deb/src/com/pku/yangliu/PorterAlgorithm.java


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