test2.save

高效的k-means算法实现

       0	[    0.744   -0.482 ] dist =   0.4408
       1	[   -0.285   0.5625 ] dist =     2.54
       2	[   0.8567      0.5 ] dist =   0.2739
       3	[   0.1775   -0.375 ] dist =   0.5544
    <stage: 23 curr: 0.1904 best: 0.1829 save: 0.1829 consecRDL: 0 >
    <End of Run>
	swapping: [     0.92     0.47 ]<-->Center[1]
       0	[   0.5671  -0.5529 ] dist =    1.098
       1	[     0.92     0.47 ] dist =    1.058
       2	[   0.2275   0.0725 ] dist =   0.3044
       3	[   0.3383   0.7733 ] dist =    1.198
    <stage: 24 curr: 0.2665 best: 0.1829 save: 0.1829 consecRDL: -0.4567 >
       0	[   0.5671  -0.5529 ] dist =    1.098
       1	[   0.8567      0.5 ] dist =   0.2886
       2	[   -0.302    0.036 ] dist =    2.749
       3	[   -0.062    0.856 ] dist =    1.194
    <stage: 25 curr: 0.1495 best: 0.1829 save: 0.1829 consecRDL: 0.439 >
       0	[   0.5338  -0.4938 ] dist =    1.393
       1	[   0.8567      0.5 ] dist =   0.2739
       2	[  -0.4525    0.065 ] dist =   0.9645
       3	[   -0.062    0.856 ] dist =   0.3584
    <stage: 26 curr: 0.143 best: 0.1829 save: 0.1829 consecRDL: 0.04376 >
    <End of Run>
	swapping: [    -0.29     0.17 ]<-->Center[2]
       0	[   0.5338  -0.4938 ] dist =    1.356
       1	[   0.8567      0.5 ] dist =   0.2739
       2	[    -0.29     0.17 ] dist =   0.8706
       3	[   -0.062    0.856 ] dist =   0.3584
    <stage: 27 curr: 0.1504 best: 0.143 save: 0.143 consecRDL: -0.05237 >
	swapping: [     0.18    -0.64 ]<-->Center[2]
       0	[   0.5338  -0.4938 ] dist =    1.356
       1	[   0.8567      0.5 ] dist =   0.2739
       2	[     0.18    -0.64 ] dist =     1.02
       3	[   -0.062    0.856 ] dist =   0.3584
    <stage: 28 curr: 0.2387 best: 0.143 save: 0.143 consecRDL: -0.5868 >
	swapping: [     0.74     0.16 ]<-->Center[3]
       0	[   0.5338  -0.4938 ] dist =    1.313
       1	[   0.8567      0.5 ] dist =   0.2739
       2	[     0.18    -0.64 ] dist =    1.543
       3	[     0.74     0.16 ] dist =    1.644
    <stage: 29 curr: 0.5265 best: 0.143 save: 0.143 consecRDL: -1.206 >
       0	[    0.624   -0.462 ] dist =   0.6558
       1	[   0.2667    0.835 ] dist =    4.467
       2	[   -0.344   -0.248 ] dist =    4.041
       3	[     0.43   0.1575 ] dist =    1.367
    <stage: 30 curr: 0.203 best: 0.143 save: 0.143 consecRDL: 0.6144 >
       0	[   0.5671  -0.5529 ] dist =    1.179
       1	[      0.1   0.8583 ] dist =    1.316
       2	[  -0.6567  0.07333 ] dist =   0.9726
       3	[     0.53   0.1475 ] dist =   0.5939
    <stage: 31 curr: 0.1581 best: 0.143 save: 0.143 consecRDL: 0.2215 >
       0	[   0.5117   -0.615 ] dist =   0.8485
       1	[      0.1   0.8583 ] dist =    1.146
       2	[  -0.6567  0.07333 ] dist =   0.3695
       3	[    0.604    0.082 ] dist =   0.7976
    <stage: 32 curr: 0.1536 best: 0.143 save: 0.143 consecRDL: 0.02862 >
    <End of Run>
	swapping: [      0.9    -0.18 ]<-->Center[3]
       0	[   0.5117   -0.615 ] dist =   0.8068
       1	[      0.1   0.8583 ] dist =    1.146
       2	[  -0.6567  0.07333 ] dist =   0.3695
       3	[      0.9    -0.18 ] dist =   0.7488
    <stage: 33 curr: 0.1794 best: 0.143 save: 0.143 consecRDL: -0.1685 >
	swapping: [      0.9    -0.18 ]<-->Center[2]
       0	[   0.5117   -0.615 ] dist =    1.469
       1	[      0.1   0.8583 ] dist =    1.146
       2	[      0.9    -0.18 ] dist =   0.3695
       3	[      0.9    -0.18 ] dist =   0.6045
    <stage: 34 curr: 0.3577 best: 0.143 save: 0.143 consecRDL: -0.9938 >
       0	[   0.3729  -0.4786 ] dist =    1.469
       1	[  -0.1522   0.5967 ] dist =    5.082
       2	[     0.87   0.0175 ] dist =   0.6045
       3	[      0.9    -0.18 ] dist =        0
    <stage: 35 curr: 0.2453 best: 0.143 save: 0.143 consecRDL: 0.3142 >
       0	[   0.3729  -0.4786 ] dist =    1.203
       1	[   -0.285   0.5625 ] dist =     2.69
       2	[   0.8567      0.5 ] dist =   0.9728
       3	[     0.91    -0.28 ] dist =   0.0404
    <stage: 36 curr: 0.2019 best: 0.143 save: 0.143 consecRDL: 0.1772 >
    <End of Run>
	swapping: [    -0.71     0.27 ]<-->Center[2]
       0	[   0.5338  -0.4938 ] dist =    1.356
       1	[   0.8567      0.5 ] dist =   0.2739
       2	[    -0.71     0.27 ] dist =   0.8706
       3	[   -0.062    0.856 ] dist =   0.3584
    <stage: 37 curr: 0.1454 best: 0.143 save: 0.143 consecRDL: -0.01682 >
	swapping: [     0.92    -0.38 ]<-->Center[2]
       0	[   0.5338  -0.4938 ] dist =    1.781
       1	[   0.8567      0.5 ] dist =   0.2739
       2	[     0.92    -0.38 ] dist =   0.4941
       3	[   -0.062    0.856 ] dist =   0.3584
    <stage: 38 curr: 0.2664 best: 0.143 save: 0.143 consecRDL: -0.8323 >
	swapping: [    -0.29     0.17 ]<-->Center[1]
       0	[   0.5338  -0.4938 ] dist =    1.386
       1	[    -0.29     0.17 ] dist =   0.2739
       2	[     0.92    -0.38 ] dist =   0.0404
       3	[   -0.062    0.856 ] dist =    3.627
    <stage: 39 curr: 0.2186 best: 0.143 save: 0.143 consecRDL: 0.1792 >
	swapping: [     0.18    -0.64 ]<-->Center[3]
       0	[   0.5338  -0.4938 ] dist =   0.9617
       1	[    -0.29     0.17 ] dist =     1.02
       2	[     0.92    -0.38 ] dist =    1.087
       3	[     0.18    -0.64 ] dist =    1.303
    <stage: 40 curr: 0.359 best: 0.143 save: 0.143 consecRDL: -0.642 >
       0	[     0.55  -0.4825 ] dist =   0.4936
       1	[  -0.2356   0.5044 ] dist =    3.992
       2	[    0.878    0.188 ] dist =    2.649
       3	[    0.125    -0.73 ] dist =   0.0445
    <stage: 41 curr: 0.2162 best: 0.143 save: 0.143 consecRDL: 0.3978 >
       0	[    0.624   -0.462 ] dist =   0.6395
       1	[  -0.2356   0.5044 ] dist =    2.958
       2	[   0.8675     0.33 ] dist =   0.7032
       3	[    0.125    -0.73 ] dist =  0.02225
    <stage: 42 curr: 0.2054 best: 0.143 save: 0.143 consecRDL: 0.04997 >
    <End of Run>
	swapping: [     0.16     0.04 ]<-->Center[3]
       0	[   0.5338  -0.4938 ] dist =    1.356
       1	[   0.8567      0.5 ] dist =   0.2739
       2	[  -0.4525    0.065 ] dist =   0.8706
       3	[     0.16     0.04 ] dist =   0.3584
    <stage: 43 curr: 0.2652 best: 0.143 save: 0.143 consecRDL: -0.8552 >
       0	[   0.5671  -0.5529 ] dist =    1.131
       1	[    0.675    0.605 ] dist =   0.9783
       2	[    -0.62      0.3 ] dist =    1.335
       3	[    0.106    0.468 ] dist =     1.86
    <stage: 44 curr: 0.1799 best: 0.143 save: 0.143 consecRDL: 0.3217 >
       0	[   0.5338  -0.4938 ] dist =    1.393
       1	[   0.8567      0.5 ] dist =   0.4059
       2	[    -0.62      0.3 ] dist =    1.002
       3	[    0.072    0.668 ] dist =   0.7967
    <stage: 45 curr: 0.1592 best: 0.143 save: 0.143 consecRDL: 0.1148 >
    <End of Run>
	swapping: [    -0.51     0.98 ]<-->Center[1]
       0	[   0.5338  -0.4938 ] dist =    1.356
       1	[    -0.51     0.98 ] dist =   0.2739
       2	[  -0.4525    0.065 ] dist =   0.8706
       3	[   -0.062    0.856 ] dist =   0.3584
    <stage: 46 curr: 0.2431 best: 0.143 save: 0.143 consecRDL: -0.7005 >
       0	[    0.593   -0.332 ] dist =    2.904
       1	[    -0.51     0.98 ] dist =        0
       2	[  -0.4525    0.065 ] dist =   0.8706
       3	[    0.222    0.834 ] dist =    1.087
    <stage: 47 curr: 0.199 best: 0.143 save: 0.143 consecRDL: 0.1816 >
    <End of Run>
	swapping: [     0.16     0.04 ]<-->Center[2]
       0	[    0.593   -0.332 ] dist =    2.183
       1	[    -0.51     0.98 ] dist =        0
       2	[     0.16     0.04 ] dist =   0.4948
       3	[    0.222    0.834 ] dist =    1.301
    <stage: 48 curr: 0.2576 best: 0.143 save: 0.143 consecRDL: -0.2945 >
       0	[   0.5887  -0.4637 ] dist =    1.708
       1	[    -0.61    0.625 ] dist =   0.5441
       2	[     -0.2  -0.0225 ] dist =    1.598
       3	[   0.3383   0.7733 ] dist =    1.301
    <stage: 49 curr: 0.204 best: 0.143 save: 0.143 consecRDL: 0.2079 >
       0	[   0.5567  -0.4211 ] dist =      1.8
       1	[    -0.61    0.625 ] dist =    0.272
       2	[  -0.3667 -0.003333 ] dist =   0.8106
       3	[   0.3383   0.7733 ] dist =    1.198
    <stage: 50 curr: 0.1985 best: 0.143 save: 0.143 consecRDL: 0.02697 >
    <End of Run>

[k-means completed:
  n_stages      = 50
  total_time    = 0.05 sec
  init_time     = 0 sec
  stage_time    = 0.001 sec/stage_(excl_init) 0.001 sec/stage_(incl_init)
  average_distort = 0.143
  (Final Center Points:
       0	[   0.5338  -0.4938 ] dist =    1.356
       1	[   0.8567      0.5 ] dist =   0.2739
       2	[  -0.4525    0.065 ] dist =   0.8706
       3	[   -0.062    0.856 ] dist =   0.3584
  )
]
  (Cluster assignments:
    Point  Center  Squared Dist
    -----  ------  ------------
       0       2      0.03743
       1       0      0.01858
       2       0       0.2326
       3       1     0.004911
       4       2       0.3758
       5       0       0.2258
       6       3      0.02682
       7       1       0.1292
       8       0       0.3215
       9       0     0.007553
      10       0       0.1465
      11       0       0.2417
      12       2        0.349
      13       1       0.1397
      14       0       0.1621
      15       2       0.1083
      16       3       0.2161
      17       3      0.04096
      18       3      0.06084
      19       3       0.0137
  )
  (Validating assignments.  Found 0 mismatches.)
<END_OF_RUN>