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 |
138.8851 |
| 2 feature(s) |
138.8851 |
NaN |
N* empirical test
| dim |
1 feature(s) |
2 feature(s) |
| 1 feature(s) |
NaN |
125.1816 |
| 2 feature(s) |
125.1816 |
NaN |
Loss Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.000044 |
0.000000 |
| 4 |
0.120375 |
0.054562 |
| 8 |
0.140078 |
0.102321 |
| 16 |
0.149305 |
0.127633 |
| 32 |
0.153728 |
0.141356 |
| 64 |
0.155492 |
0.148285 |
| 128 |
0.157941 |
0.152899 |
| 256 |
0.158279 |
0.154449 |
| 512 |
0.158191 |
0.154943 |
| 1024 |
0.158670 |
0.155880 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.188307 |
0.296273 |
| 4 |
0.184946 |
0.266811 |
| 8 |
0.177639 |
0.225377 |
| 16 |
0.169843 |
0.192701 |
| 32 |
0.164379 |
0.173430 |
| 64 |
0.161758 |
0.164723 |
| 128 |
0.160186 |
0.160352 |
| 256 |
0.159371 |
0.158127 |
| 512 |
0.158992 |
0.157175 |
| 1024 |
0.158849 |
0.156749 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.252933 |
0.462951 |
| 4 |
0.205438 |
0.330086 |
| 8 |
0.179973 |
0.237195 |
| 16 |
0.169839 |
0.193265 |
| 32 |
0.164467 |
0.173730 |
| 64 |
0.161755 |
0.164641 |
| 128 |
0.160254 |
0.160158 |
| 256 |
0.159717 |
0.158304 |
| 512 |
0.159192 |
0.157446 |
| 1024 |
0.158736 |
0.156625 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
0.147997 |
| THEORETICAL |
0.081650 |
| EMPIRICAL_TEST |
0.149262 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
0.072103 |
| 2 |
0.112718 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
0.038566 |
| 1 |
0.028101 |
| 2 |
0.018718 |
| 3 |
0.013893 |
| 4 |
0.010878 |
| 5 |
0.009335 |
| 6 |
0.009511 |
| 7 |
0.012779 |
| 8 |
0.024325 |
| 9 |
0.056091 |
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 |
11978 |
| 4 |
11440 |
15360 |
| 8 |
8008 |
7952 |
| 16 |
5240 |
4560 |
| 32 |
2828 |
4032 |
| 64 |
2160 |
2360 |
| 128 |
1806 |
1526 |
| 256 |
1010 |
1080 |
| 512 |
707 |
721 |
| 1024 |
515 |
525 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
22600 |
20905 |
| 4 |
14640 |
12960 |
| 8 |
8232 |
7336 |
| 16 |
6440 |
4280 |
| 32 |
3696 |
2828 |
| 64 |
2500 |
2400 |
| 128 |
1610 |
1568 |
| 256 |
1070 |
1010 |
| 512 |
1092 |
987 |
| 1024 |
640 |
640 |