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 |
77.7232 |
| 2 feature(s) |
77.7232 |
NaN |
N* empirical test
| dim |
1 feature(s) |
2 feature(s) |
| 1 feature(s) |
NaN |
75.5621 |
| 2 feature(s) |
75.5621 |
NaN |
Loss Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.000044 |
0.000000 |
| 4 |
0.120375 |
0.054891 |
| 8 |
0.140078 |
0.100469 |
| 16 |
0.149305 |
0.125719 |
| 32 |
0.153728 |
0.139286 |
| 64 |
0.155492 |
0.146148 |
| 128 |
0.157941 |
0.150525 |
| 256 |
0.158279 |
0.151920 |
| 512 |
0.158191 |
0.152473 |
| 1024 |
0.158670 |
0.153330 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.188307 |
0.289915 |
| 4 |
0.184946 |
0.261370 |
| 8 |
0.177639 |
0.221826 |
| 16 |
0.169843 |
0.190139 |
| 32 |
0.164379 |
0.170869 |
| 64 |
0.161758 |
0.162600 |
| 128 |
0.160186 |
0.158026 |
| 256 |
0.159371 |
0.155814 |
| 512 |
0.158992 |
0.154877 |
| 1024 |
0.158849 |
0.154437 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.252933 |
0.439186 |
| 4 |
0.205438 |
0.317308 |
| 8 |
0.179973 |
0.232478 |
| 16 |
0.169839 |
0.190675 |
| 32 |
0.164467 |
0.171194 |
| 64 |
0.161755 |
0.162568 |
| 128 |
0.160254 |
0.157673 |
| 256 |
0.159717 |
0.155805 |
| 512 |
0.159192 |
0.154747 |
| 1024 |
0.158736 |
0.154254 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
0.133583 |
| THEORETICAL |
0.078996 |
| EMPIRICAL_TEST |
0.145106 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
0.074949 |
| 2 |
0.097484 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
0.040310 |
| 1 |
0.030408 |
| 2 |
0.019379 |
| 3 |
0.014916 |
| 4 |
0.010607 |
| 5 |
0.008826 |
| 6 |
0.008728 |
| 7 |
0.011882 |
| 8 |
0.020115 |
| 9 |
0.046333 |
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 |
21583 |
| 4 |
11440 |
9840 |
| 8 |
8008 |
10808 |
| 16 |
5240 |
4440 |
| 32 |
2828 |
4172 |
| 64 |
2160 |
2160 |
| 128 |
1806 |
1750 |
| 256 |
1010 |
1080 |
| 512 |
707 |
756 |
| 1024 |
515 |
520 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
22600 |
17176 |
| 4 |
14640 |
16000 |
| 8 |
8232 |
7336 |
| 16 |
6440 |
4640 |
| 32 |
3696 |
2996 |
| 64 |
2500 |
2160 |
| 128 |
1610 |
1568 |
| 256 |
1070 |
1620 |
| 512 |
1092 |
749 |
| 1024 |
640 |
685 |