sample.save

高效的k-means算法实现

Data Points:
(-0.297462, 0.176102)
(0.565538, -0.361496)
(0.909313, -0.182785)
(0.920712, 0.478408)
(0.167682, 0.0499836)
(0.305223, -0.0805835)
(0.114973, 0.882453)
(0.742916, 0.16376)
(0.0724605, -0.826775)
(0.69096, -0.559284)
(0.188485, -0.643934)
(0.749427, -0.942415)
(-0.970662, -0.223466)
(0.91611, 0.879597)
(0.927417, -0.382593)
(-0.711327, 0.278713)
(-0.519172, 0.986146)
(0.135338, 0.924588)
(-0.0837537, 0.61687)
(0.0520465, 0.896306)

Executing Clustering Algorithm: Lloyd's
Number of stages: 100
Average distortion: 0.140324
(Final Center Points:
       0	[ -0.659817 0.0771163 ] dist = 0.371368
       1	[ 0.508501 -0.436654 ] dist =  1.78337
       2	[ 0.859913 0.507255 ] dist = 0.278002
       3	[ -0.0601136 0.861273 ] dist = 0.373741
)
(Cluster assignments:
    Point  Center  Squared Dist
    -----  ------  ------------
       0       0     0.141099
       1       1   0.00890192
       2       1       0.2251
       3       2   0.00452871
       4       1     0.352973
       5       1     0.168108
       6       3    0.0311039
       7       2     0.131677
       8       1     0.342326
       9       1    0.0483297
      10       1     0.145375
      11       1      0.31384
      12       0     0.186974
      13       2     0.141797
      14       1     0.178413
      15       0    0.0432945
      16       3     0.226328
      17       3    0.0422102
      18       3    0.0602915
      19       3    0.0138072
)

Executing Clustering Algorithm: Swap
Number of stages: 100
Average distortion: 0.189847
(Final Center Points:
       0	[ 0.0520465 0.896306 ] dist = 0.442777
       1	[ -0.970662 -0.223466 ] dist = 0.932291
       2	[ 0.742916  0.16376 ] dist =  1.41593
       3	[  0.69096 -0.559284 ] dist =  1.00593
)
(Cluster assignments:
    Point  Center  Squared Dist
    -----  ------  ------------
       0       1     0.612853
       1       3    0.0548508
       2       2     0.147781
       3       2     0.130615
       4       2     0.343839
       5       2     0.251279
       6       0   0.00415165
       7       2            0
       8       3     0.454093
       9       3            0
      10       3     0.259647
      11       3     0.150208
      12       1            0
      13       2     0.542419
      14       3    0.0871316
      15       1     0.319438
      16       0     0.334362
      17       0   0.00773735
      18       0    0.0965262
      19       0            0
)

Executing Clustering Algorithm: EZ-Hybrid
Number of stages: 102
Average distortion: 0.140324
(Final Center Points:
       0	[ 0.859913 0.507255 ] dist = 0.278002
       1	[ -0.0601136 0.861273 ] dist = 0.373741
       2	[ 0.508501 -0.436654 ] dist =  1.78337
       3	[ -0.659817 0.0771163 ] dist = 0.371368
)
(Cluster assignments:
    Point  Center  Squared Dist
    -----  ------  ------------
       0       3     0.141099
       1       2   0.00890192
       2       2       0.2251
       3       0   0.00452871
       4       2     0.352973
       5       2     0.168108
       6       1    0.0311039
       7       0     0.131677
       8       2     0.342326
       9       2    0.0483297
      10       2     0.145375
      11       2      0.31384
      12       3     0.186974
      13       0     0.141797
      14       2     0.178413
      15       3    0.0432945
      16       1     0.226328
      17       1    0.0422102
      18       1    0.0602915
      19       1    0.0138072
)

Executing Clustering Algorithm: Hybrid
Number of stages: 101
Average distortion: 0.140324
(Final Center Points:
       0	[ -0.659817 0.0771163 ] dist = 0.371368
       1	[ -0.0601136 0.861273 ] dist = 0.373741
       2	[ 0.859913 0.507255 ] dist = 0.278002
       3	[ 0.508501 -0.436654 ] dist =  1.78337
)
(Cluster assignments:
    Point  Center  Squared Dist
    -----  ------  ------------
       0       0     0.141099
       1       3   0.00890192
       2       3       0.2251
       3       2   0.00452871
       4       3     0.352973
       5       3     0.168108
       6       1    0.0311039
       7       2     0.131677
       8       3     0.342326
       9       3    0.0483297
      10       3     0.145375
      11       3      0.31384
      12       0     0.186974
      13       2     0.141797
      14       3     0.178413
      15       0    0.0432945
      16       1     0.226328
      17       1    0.0422102
      18       1    0.0602915
      19       1    0.0138072
)