Simulation Visualizations
Loss vs log_2(n)
Loss vs log(n) EMPIRICAL_TRAIN

Loss vs log(n) THEORETICAL

Loss vs log(n) EMPIRICAL_TEST

Loss vs log(n) 1 features

Loss vs log(n) 2 features

Time consumption(n)
Iterations vs log_2(n)
Iterations vs log(n) EMPIRICAL_TRAIN

Iterations vs log(n) THEORETICAL

Iterations vs log(n) EMPIRICAL_TEST

Iterations vs log(n) 1 features

Iterations vs log(n) 2 features

N* Relationship Matrixes
N* theoretical
| dim |
1 feature(s) |
2 feature(s) |
| 1 feature(s) |
NaN |
NaN |
| 2 feature(s) |
NaN |
NaN |
N* empirical test
| dim |
1 feature(s) |
2 feature(s) |
| 1 feature(s) |
NaN |
NaN |
| 2 feature(s) |
NaN |
NaN |
Loss Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.000000 |
0.000000 |
| 4 |
0.119766 |
0.030422 |
| 8 |
0.140301 |
0.046931 |
| 16 |
0.149586 |
0.058969 |
| 32 |
0.153789 |
0.066652 |
| 64 |
0.156527 |
0.072234 |
| 128 |
0.157037 |
0.075148 |
| 256 |
0.157387 |
0.076863 |
| 512 |
0.157867 |
0.077437 |
| 1024 |
0.158099 |
0.078300 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.188071 |
0.149846 |
| 4 |
0.185518 |
0.139034 |
| 8 |
0.177590 |
0.119695 |
| 16 |
0.169889 |
0.102493 |
| 32 |
0.164506 |
0.091845 |
| 64 |
0.161720 |
0.085576 |
| 128 |
0.160137 |
0.082285 |
| 256 |
0.159419 |
0.080447 |
| 512 |
0.159051 |
0.079580 |
| 1024 |
0.158865 |
0.079115 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.253412 |
0.171709 |
| 4 |
0.206302 |
0.145717 |
| 8 |
0.180396 |
0.120311 |
| 16 |
0.170165 |
0.102530 |
| 32 |
0.164619 |
0.091807 |
| 64 |
0.161913 |
0.085604 |
| 128 |
0.160289 |
0.082098 |
| 256 |
0.159345 |
0.080364 |
| 512 |
0.158782 |
0.079433 |
| 1024 |
0.158499 |
0.078894 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
0.107819 |
| THEORETICAL |
0.068102 |
| EMPIRICAL_TEST |
0.127068 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
0.082558 |
| 2 |
0.066048 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
0.034962 |
| 1 |
0.030426 |
| 2 |
0.022019 |
| 3 |
0.015401 |
| 4 |
0.012322 |
| 5 |
0.010958 |
| 6 |
0.009422 |
| 7 |
0.010018 |
| 8 |
0.014443 |
| 9 |
0.031150 |
Iterations Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
11413 |
11413 |
| 4 |
16000 |
16000 |
| 8 |
11200 |
11200 |
| 16 |
8000 |
8000 |
| 32 |
5600 |
5600 |
| 64 |
4000 |
4000 |
| 128 |
2800 |
2800 |
| 256 |
2000 |
2000 |
| 512 |
1400 |
1400 |
| 1024 |
1000 |
1000 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
12995 |
17967 |
| 4 |
9920 |
16000 |
| 8 |
10192 |
9016 |
| 16 |
5040 |
5720 |
| 32 |
3388 |
3052 |
| 64 |
2120 |
2420 |
| 128 |
1456 |
1470 |
| 256 |
1100 |
1100 |
| 512 |
707 |
707 |
| 1024 |
510 |
505 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
22600 |
15255 |
| 4 |
16000 |
12160 |
| 8 |
6720 |
6048 |
| 16 |
4120 |
5800 |
| 32 |
4732 |
4928 |
| 64 |
2400 |
2800 |
| 128 |
2436 |
1484 |
| 256 |
1570 |
1010 |
| 512 |
763 |
721 |
| 1024 |
600 |
640 |