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 |
110.2958 |
| 2 feature(s) |
110.2958 |
NaN |
N* empirical test
| dim |
1 feature(s) |
2 feature(s) |
| 1 feature(s) |
NaN |
108.014 |
| 2 feature(s) |
108.014 |
NaN |
Loss Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.000044 |
0.000000 |
| 4 |
0.120375 |
0.054828 |
| 8 |
0.140078 |
0.101217 |
| 16 |
0.149305 |
0.126906 |
| 32 |
0.153728 |
0.140569 |
| 64 |
0.155492 |
0.147527 |
| 128 |
0.157941 |
0.151998 |
| 256 |
0.158279 |
0.153559 |
| 512 |
0.158191 |
0.153983 |
| 1024 |
0.158670 |
0.154919 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.188307 |
0.294153 |
| 4 |
0.184946 |
0.264657 |
| 8 |
0.177639 |
0.223672 |
| 16 |
0.169843 |
0.191373 |
| 32 |
0.164379 |
0.172422 |
| 64 |
0.161758 |
0.163892 |
| 128 |
0.160186 |
0.159603 |
| 256 |
0.159371 |
0.157235 |
| 512 |
0.158992 |
0.156323 |
| 1024 |
0.158849 |
0.155883 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.252933 |
0.453231 |
| 4 |
0.205438 |
0.324631 |
| 8 |
0.179973 |
0.235198 |
| 16 |
0.169839 |
0.192224 |
| 32 |
0.164467 |
0.172477 |
| 64 |
0.161755 |
0.163804 |
| 128 |
0.160254 |
0.159589 |
| 256 |
0.159717 |
0.157379 |
| 512 |
0.159192 |
0.156468 |
| 1024 |
0.158736 |
0.155789 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
0.141307 |
| THEORETICAL |
0.086830 |
| EMPIRICAL_TEST |
0.150182 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
0.074053 |
| 2 |
0.108184 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
0.039673 |
| 1 |
0.030473 |
| 2 |
0.019713 |
| 3 |
0.015093 |
| 4 |
0.011571 |
| 5 |
0.009066 |
| 6 |
0.009286 |
| 7 |
0.012556 |
| 8 |
0.022313 |
| 9 |
0.051114 |
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 |
21696 |
| 4 |
11440 |
16000 |
| 8 |
8008 |
6888 |
| 16 |
5240 |
8000 |
| 32 |
2828 |
3892 |
| 64 |
2160 |
2360 |
| 128 |
1806 |
1750 |
| 256 |
1010 |
1080 |
| 512 |
707 |
784 |
| 1024 |
515 |
545 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
22600 |
19097 |
| 4 |
14640 |
16000 |
| 8 |
8232 |
8456 |
| 16 |
6440 |
4680 |
| 32 |
3696 |
3892 |
| 64 |
2500 |
2420 |
| 128 |
1610 |
2086 |
| 256 |
1070 |
1850 |
| 512 |
1092 |
910 |
| 1024 |
640 |
525 |