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 |
111.0623 |
| 2 feature(s) |
111.0623 |
NaN |
N* empirical test
| dim |
1 feature(s) |
2 feature(s) |
| 1 feature(s) |
NaN |
107.2657 |
| 2 feature(s) |
107.2657 |
NaN |
Loss Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.000000 |
0.000000 |
| 4 |
0.119000 |
0.059984 |
| 8 |
0.141060 |
0.104286 |
| 16 |
0.148336 |
0.127734 |
| 32 |
0.153064 |
0.141088 |
| 64 |
0.155500 |
0.147645 |
| 128 |
0.157461 |
0.151900 |
| 256 |
0.157725 |
0.153334 |
| 512 |
0.157927 |
0.153825 |
| 1024 |
0.158268 |
0.154755 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.188349 |
0.283228 |
| 4 |
0.185134 |
0.259686 |
| 8 |
0.177937 |
0.222483 |
| 16 |
0.169385 |
0.191380 |
| 32 |
0.164430 |
0.172684 |
| 64 |
0.161781 |
0.164249 |
| 128 |
0.160130 |
0.159495 |
| 256 |
0.159404 |
0.157400 |
| 512 |
0.159022 |
0.156414 |
| 1024 |
0.158852 |
0.155988 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.251980 |
0.422497 |
| 4 |
0.206474 |
0.311960 |
| 8 |
0.180069 |
0.233186 |
| 16 |
0.169696 |
0.191887 |
| 32 |
0.164493 |
0.172711 |
| 64 |
0.161580 |
0.163916 |
| 128 |
0.160020 |
0.159221 |
| 256 |
0.159199 |
0.157271 |
| 512 |
0.158640 |
0.156234 |
| 1024 |
0.158548 |
0.155783 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
8.128217 |
| THEORETICAL |
5.176867 |
| EMPIRICAL_TEST |
9.971846 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
4.944432 |
| 2 |
6.154085 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
2.699237 |
| 1 |
1.887624 |
| 2 |
1.506127 |
| 3 |
0.928639 |
| 4 |
0.772476 |
| 5 |
0.552594 |
| 6 |
0.603075 |
| 7 |
0.724126 |
| 8 |
1.225225 |
| 9 |
2.854694 |
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 |
16611 |
21131 |
| 4 |
11680 |
14000 |
| 8 |
6496 |
5768 |
| 16 |
6240 |
8000 |
| 32 |
2968 |
3612 |
| 64 |
2480 |
2160 |
| 128 |
1428 |
1498 |
| 256 |
1010 |
1090 |
| 512 |
707 |
777 |
| 1024 |
505 |
505 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
22600 |
21583 |
| 4 |
16000 |
11440 |
| 8 |
9296 |
8680 |
| 16 |
4160 |
5680 |
| 32 |
3780 |
3892 |
| 64 |
2620 |
2460 |
| 128 |
2170 |
1554 |
| 256 |
1020 |
1050 |
| 512 |
840 |
882 |
| 1024 |
640 |
1000 |