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 |
29.1727 |
| 2 feature(s) |
29.1727 |
NaN |
N* empirical test
| dim |
1 feature(s) |
2 feature(s) |
| 1 feature(s) |
NaN |
28.9661 |
| 2 feature(s) |
28.9661 |
NaN |
Loss Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.000044 |
0.000000 |
| 4 |
0.120375 |
0.053297 |
| 8 |
0.140078 |
0.094453 |
| 16 |
0.149305 |
0.118164 |
| 32 |
0.153728 |
0.131367 |
| 64 |
0.155492 |
0.138113 |
| 128 |
0.157941 |
0.142363 |
| 256 |
0.158279 |
0.143871 |
| 512 |
0.158191 |
0.144494 |
| 1024 |
0.158670 |
0.145196 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.188307 |
0.266744 |
| 4 |
0.184946 |
0.244807 |
| 8 |
0.177639 |
0.210197 |
| 16 |
0.169843 |
0.180266 |
| 32 |
0.164379 |
0.162774 |
| 64 |
0.161758 |
0.154404 |
| 128 |
0.160186 |
0.149858 |
| 256 |
0.159371 |
0.147874 |
| 512 |
0.158992 |
0.146874 |
| 1024 |
0.158849 |
0.146455 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.252933 |
0.377799 |
| 4 |
0.205438 |
0.285746 |
| 8 |
0.179973 |
0.218499 |
| 16 |
0.169839 |
0.180665 |
| 32 |
0.164467 |
0.162650 |
| 64 |
0.161755 |
0.154224 |
| 128 |
0.160254 |
0.149877 |
| 256 |
0.159717 |
0.147586 |
| 512 |
0.159192 |
0.146486 |
| 1024 |
0.158736 |
0.146011 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
0.120467 |
| THEORETICAL |
0.067723 |
| EMPIRICAL_TEST |
0.136362 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
0.075670 |
| 2 |
0.083136 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
0.037588 |
| 1 |
0.029605 |
| 2 |
0.018596 |
| 3 |
0.015015 |
| 4 |
0.011760 |
| 5 |
0.009111 |
| 6 |
0.008907 |
| 7 |
0.010189 |
| 8 |
0.017140 |
| 9 |
0.039779 |
Iterations Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
22600 |
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 |
12656 |
11526 |
| 4 |
11440 |
15520 |
| 8 |
8008 |
6104 |
| 16 |
5240 |
5560 |
| 32 |
2828 |
4004 |
| 64 |
2160 |
2720 |
| 128 |
1806 |
1526 |
| 256 |
1010 |
1090 |
| 512 |
707 |
714 |
| 1024 |
515 |
545 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
22600 |
18419 |
| 4 |
14640 |
16000 |
| 8 |
8232 |
5936 |
| 16 |
6440 |
5520 |
| 32 |
3696 |
5404 |
| 64 |
2500 |
2360 |
| 128 |
1610 |
2506 |
| 256 |
1070 |
1420 |
| 512 |
1092 |
763 |
| 1024 |
640 |
540 |