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 |
0.117719 |
0.010922 |
| 8 |
0.140290 |
0.018326 |
| 16 |
0.148930 |
0.023664 |
| 32 |
0.153984 |
0.027483 |
| 64 |
0.156566 |
0.029699 |
| 128 |
0.157679 |
0.031532 |
| 256 |
0.157908 |
0.032232 |
| 512 |
0.158193 |
0.033013 |
| 1024 |
0.158333 |
0.033401 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.187967 |
0.121753 |
| 4 |
0.184876 |
0.093416 |
| 8 |
0.177253 |
0.070270 |
| 16 |
0.169677 |
0.053756 |
| 32 |
0.164352 |
0.044452 |
| 64 |
0.161657 |
0.039644 |
| 128 |
0.160146 |
0.036979 |
| 256 |
0.159367 |
0.035566 |
| 512 |
0.159017 |
0.034763 |
| 1024 |
0.158872 |
0.034349 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.251457 |
0.133602 |
| 4 |
0.204727 |
0.095687 |
| 8 |
0.180736 |
0.070534 |
| 16 |
0.169710 |
0.053857 |
| 32 |
0.164599 |
0.044603 |
| 64 |
0.161982 |
0.039507 |
| 128 |
0.160454 |
0.036947 |
| 256 |
0.159338 |
0.035486 |
| 512 |
0.159107 |
0.034791 |
| 1024 |
0.158899 |
0.034172 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
0.086832 |
| THEORETICAL |
0.052045 |
| EMPIRICAL_TEST |
0.103704 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
0.067677 |
| 2 |
0.051287 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
0.027675 |
| 1 |
0.028853 |
| 2 |
0.020706 |
| 3 |
0.014163 |
| 4 |
0.009741 |
| 5 |
0.007301 |
| 6 |
0.006566 |
| 7 |
0.006931 |
| 8 |
0.010526 |
| 9 |
0.022537 |
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 |
19323 |
| 4 |
8160 |
11920 |
| 8 |
6720 |
7056 |
| 16 |
5040 |
6040 |
| 32 |
2940 |
3052 |
| 64 |
2280 |
2020 |
| 128 |
1442 |
1456 |
| 256 |
1010 |
1060 |
| 512 |
728 |
735 |
| 1024 |
510 |
510 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
13786 |
15594 |
| 4 |
16000 |
14960 |
| 8 |
11200 |
7448 |
| 16 |
4760 |
5400 |
| 32 |
2940 |
4228 |
| 64 |
2140 |
2040 |
| 128 |
2086 |
1484 |
| 256 |
1030 |
1270 |
| 512 |
777 |
938 |
| 1024 |
560 |
530 |