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 |
3.4036 |
| 2 feature(s) |
3.4036 |
NaN |
N* empirical test
| dim |
1 feature(s) |
2 feature(s) |
| 1 feature(s) |
NaN |
3.6434 |
| 2 feature(s) |
3.6434 |
NaN |
Loss Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.000000 |
0.000000 |
| 4 |
0.117641 |
0.007766 |
| 8 |
0.139900 |
0.013650 |
| 16 |
0.149227 |
0.016039 |
| 32 |
0.154314 |
0.017690 |
| 64 |
0.156898 |
0.018984 |
| 128 |
0.157586 |
0.020259 |
| 256 |
0.158143 |
0.020566 |
| 512 |
0.158210 |
0.021102 |
| 1024 |
0.158392 |
0.021446 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.187976 |
0.271802 |
| 4 |
0.185379 |
0.159921 |
| 8 |
0.177345 |
0.077595 |
| 16 |
0.169636 |
0.044258 |
| 32 |
0.164262 |
0.032199 |
| 64 |
0.161664 |
0.026976 |
| 128 |
0.160151 |
0.024608 |
| 256 |
0.159355 |
0.023320 |
| 512 |
0.159021 |
0.022674 |
| 1024 |
0.158869 |
0.022292 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.252362 |
0.390518 |
| 4 |
0.204733 |
0.183227 |
| 8 |
0.180258 |
0.078854 |
| 16 |
0.169740 |
0.044173 |
| 32 |
0.164570 |
0.032231 |
| 64 |
0.161948 |
0.026963 |
| 128 |
0.160272 |
0.024618 |
| 256 |
0.159371 |
0.023252 |
| 512 |
0.159163 |
0.022689 |
| 1024 |
0.158893 |
0.022196 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
5.366430 |
| THEORETICAL |
3.441718 |
| EMPIRICAL_TEST |
6.619588 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
4.161778 |
| 2 |
3.297386 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
2.041480 |
| 1 |
1.679920 |
| 2 |
1.107210 |
| 3 |
0.754512 |
| 4 |
0.568331 |
| 5 |
0.443164 |
| 6 |
0.369915 |
| 7 |
0.418861 |
| 8 |
0.679660 |
| 9 |
1.574861 |
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 |
13221 |
16385 |
| 4 |
13360 |
16000 |
| 8 |
8400 |
9352 |
| 16 |
4160 |
4520 |
| 32 |
3360 |
4256 |
| 64 |
2280 |
2020 |
| 128 |
1498 |
1456 |
| 256 |
1010 |
1040 |
| 512 |
721 |
728 |
| 1024 |
505 |
505 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
22600 |
11865 |
| 4 |
16000 |
16000 |
| 8 |
6384 |
11200 |
| 16 |
4600 |
5800 |
| 32 |
3976 |
2968 |
| 64 |
2300 |
2060 |
| 128 |
1428 |
1428 |
| 256 |
1030 |
1110 |
| 512 |
959 |
945 |
| 1024 |
580 |
580 |