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 |
50.8068 |
| 2 feature(s) |
50.8068 |
NaN |
N* empirical test
| dim |
1 feature(s) |
2 feature(s) |
| 1 feature(s) |
NaN |
50.5876 |
| 2 feature(s) |
50.5876 |
NaN |
Loss Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.000044 |
0.000000 |
| 4 |
0.120375 |
0.054875 |
| 8 |
0.140078 |
0.098025 |
| 16 |
0.149305 |
0.123438 |
| 32 |
0.153728 |
0.136696 |
| 64 |
0.155492 |
0.143488 |
| 128 |
0.157941 |
0.147866 |
| 256 |
0.158279 |
0.149078 |
| 512 |
0.158191 |
0.149669 |
| 1024 |
0.158670 |
0.150737 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.188307 |
0.281838 |
| 4 |
0.184946 |
0.256127 |
| 8 |
0.177639 |
0.218198 |
| 16 |
0.169843 |
0.186937 |
| 32 |
0.164379 |
0.168297 |
| 64 |
0.161758 |
0.159802 |
| 128 |
0.160186 |
0.155374 |
| 256 |
0.159371 |
0.153266 |
| 512 |
0.158992 |
0.152272 |
| 1024 |
0.158849 |
0.151849 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.252933 |
0.416363 |
| 4 |
0.205438 |
0.305713 |
| 8 |
0.179973 |
0.227502 |
| 16 |
0.169839 |
0.187619 |
| 32 |
0.164467 |
0.168381 |
| 64 |
0.161755 |
0.159745 |
| 128 |
0.160254 |
0.154947 |
| 256 |
0.159717 |
0.153136 |
| 512 |
0.159192 |
0.152071 |
| 1024 |
0.158736 |
0.151528 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
0.121570 |
| THEORETICAL |
0.076387 |
| EMPIRICAL_TEST |
0.137339 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
0.073351 |
| 2 |
0.089175 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
0.039590 |
| 1 |
0.030258 |
| 2 |
0.020936 |
| 3 |
0.013395 |
| 4 |
0.010712 |
| 5 |
0.008430 |
| 6 |
0.007803 |
| 7 |
0.009881 |
| 8 |
0.018447 |
| 9 |
0.041126 |
Iterations Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
22600 |
11413 |
| 4 |
16000 |
16000 |
| 8 |
11200 |
11200 |
| 16 |
8000 |
4760 |
| 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 |
22600 |
| 4 |
11440 |
13120 |
| 8 |
8008 |
11200 |
| 16 |
5240 |
8000 |
| 32 |
2828 |
4228 |
| 64 |
2160 |
2700 |
| 128 |
1806 |
1960 |
| 256 |
1010 |
1010 |
| 512 |
707 |
742 |
| 1024 |
515 |
505 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
22600 |
16837 |
| 4 |
14640 |
16000 |
| 8 |
8232 |
11200 |
| 16 |
6440 |
4680 |
| 32 |
3696 |
5152 |
| 64 |
2500 |
2680 |
| 128 |
1610 |
1470 |
| 256 |
1070 |
1090 |
| 512 |
1092 |
875 |
| 1024 |
640 |
520 |