OUTPUT of run 7 of at most 100:
```
MLP NEURON NORM QUANTILES: input row / output column
0 [0.3266 0.3623 0.3895 0.4232 0.9669 2.6887 4.4219] [0.1318 0.1623 0.194  0.2373 1.2717 2.154  4.7954]
1 [0.3913 1.7931 1.9056 2.004  2.1051 2.2776 3.3711] [0.1986 1.7341 1.8466 1.9219 2.0072 2.1576 2.6756]
2 [1.7221 1.9046 1.9707 2.0103 2.0551 2.1253 2.4825] [1.5505 1.7804 1.8885 1.9574 2.0251 2.1289 2.4465]
3 [1.7763 1.8813 1.9381 1.9761 2.014  2.0986 3.1298] [1.4454 1.735  1.9208 2.0615 2.2221 2.491  4.8197]

LAST MLP OUTPUT-COLUMN GEOMETRY
nearest cosine percentiles: [0.459  0.5382 0.5696 0.605  0.6485 0.7103 0.9073 0.9462]
k 20 inertia 1139.135
cluster sizes [107  96  89  88  87  85  84  83  81  78  74  74  73  71  69  68  66  64  52  47]
centroid norms [0.7   0.475 0.529 0.49  0.448 0.475 0.5   0.508 0.465 0.497 0.502 0.469 0.499 0.491 0.481 0.491 0.505 0.471 0.481 0.57 ]
k 24 inertia 1117.005
cluster sizes [93 79 77 74 73 72 70 67 66 66 66 66 65 58 58 58 57 57 57 56 54 51 48 48]
centroid norms [0.6   0.726 0.511 0.435 0.501 0.508 0.458 0.507 0.485 0.528 0.5   0.564 0.485 0.506 0.488 0.5   0.507 0.477 0.486 0.513 0.523 0.517 0.519 0.54 ]
k 28 inertia 1095.936
cluster sizes [78 76 73 68 63 63 62 61 59 58 58 55 55 55 53 52 51 50 49 48 48 47 46 44 43 43 40 38]
centroid norms [0.725 0.653 0.504 0.506 0.511 0.505 0.533 0.588 0.479 0.508 0.488 0.496 0.5   0.524 0.493 0.548 0.456 0.556 0.499 0.517 0.532 0.522 0.492 0.508 0.5   0.502 0.522 0.602]
k 32 inertia 1077.692
cluster sizes [74 61 61 59 57 57 55 52 52 50 48 48 48 48 47 46 46 46 44 44 43 43 43 42 42 42 41 41 41 41 38 36]
centroid norms [0.72  0.481 0.499 0.487 0.545 0.698 0.532 0.518 0.514 0.542 0.503 0.54  0.55  0.566 0.532 0.553 0.537 0.502 0.513 0.56  0.543 0.512 0.489 0.49  0.53  0.519 0.557 0.5   0.662
 0.498 0.517 0.57 ]

INDEPENDENT-COMPONENT DECOMPOSITION OF OUTPUT WEIGHT COLUMNS
components 24 iterations 660
excess kurtoses [ 4.353  1.607  1.307  1.306  1.246  1.156  1.15   1.028  1.002  0.996  0.884  0.875  0.83   0.809  0.798 -0.443 -0.46  -0.493 -0.554 -0.576 -0.583 -0.591 -0.62  -0.673]
absolute skewness [0.368 0.464 0.003 0.307 0.177 0.08  0.234 0.22  0.08  0.157 0.179 0.084 0.3   0.13  0.094 0.141 0.069 0.055 0.023 0.086 0.01  0.006 0.053 0.139]
components 28 iterations 1416
excess kurtoses [37.202  4.452  1.572  1.357  1.232  1.232  1.154  1.153  1.131  1.131  1.083  1.049  0.934  0.925  0.876  0.854  0.795  0.789  0.779  0.745 -0.517 -0.566 -0.576 -0.58  -0.587
 -0.605 -0.626 -0.702]
absolute skewness [0.607 0.415 0.422 0.155 0.142 0.278 0.443 0.171 0.027 0.256 0.128 0.283 0.124 0.174 0.107 0.012 0.    0.076 0.211 0.181 0.074 0.119 0.085 0.056 0.121 0.082 0.017 0.057]

INDUCTION-CANDIDATE MATRIX EIGENVALUES
eigenvalues descending magnitude [ 0.0505+0.0128j  0.0505-0.0128j  0.0423+0.j      0.0356+0.0108j  0.0356-0.0108j  0.0321+0.j      0.0306+0.0061j  0.0306-0.0061j  0.0269+0.0028j  0.0269-0.0028j  0.0151+0.0061j
  0.0151-0.0061j  0.0139+0.j      0.0117+0.j      0.0056+0.0101j  0.0056-0.0101j  0.0085+0.j      0.0019+0.005j   0.0019-0.005j   0.0037+0.0019j  0.0037-0.0019j -0.0019+0.0034j
 -0.0019-0.0034j  0.0034+0.j     -0.0022+0.0025j -0.0022-0.0025j  0.0019+0.0022j  0.0019-0.0022j -0.0025+0.0002j -0.0025-0.0002j -0.0021+0.j     -0.0015-0.0006j -0.0015+0.0006j
  0.0008+0.0012j  0.0008-0.0012j  0.0009+0.j     -0.0003+0.0007j -0.0003-0.0007j  0.0006+0.0002j  0.0006-0.0002j  0.0006+0.j      0.0002+0.0005j  0.0002-0.0005j  0.0003+0.0003j
  0.0003-0.0003j -0.0002+0.0004j -0.0002-0.0004j -0.0003+0.j      0.    -0.0002j  0.    +0.0002j -0.0002+0.j      0.0001+0.j      0.0001-0.j     -0.0001+0.j     -0.0001-0.j
  0.0001+0.j     -0.    +0.0001j -0.    -0.0001j  0.0001+0.j      0.0001-0.j      0.    +0.j     -0.    +0.j     -0.    +0.j     -0.    +0.j    ]
symmetric-part eigenvalues descending [ 0.0673  0.0527  0.0511  0.0468  0.0452  0.0421  0.0364  0.0329  0.0319  0.0281  0.0273  0.0188  0.0175  0.0171  0.0125  0.0103  0.0077  0.0063  0.0058  0.0044  0.0042  0.0027
  0.0024  0.0021  0.0014  0.0012  0.001   0.001   0.0008  0.0004  0.0003  0.0002  0.0001  0.0001 -0.0002 -0.0003 -0.0003 -0.0005 -0.0006 -0.0007 -0.0009 -0.0012 -0.0014 -0.0017
 -0.0018 -0.002  -0.0024 -0.0025 -0.0028 -0.0029 -0.0036 -0.0041 -0.0046 -0.005  -0.0052 -0.0059 -0.0073 -0.0084 -0.0086 -0.0098 -0.0103 -0.0126 -0.0142 -0.0173]

```