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 |
12.5538 |
| 2 feature(s) |
12.5538 |
NaN |
N* empirical test
| dim |
1 feature(s) |
2 feature(s) |
| 1 feature(s) |
NaN |
12.9292 |
| 2 feature(s) |
12.9292 |
NaN |
Loss Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.000044 |
0.000000 |
| 4 |
0.120375 |
0.049203 |
| 8 |
0.140078 |
0.083817 |
| 16 |
0.149305 |
0.105125 |
| 32 |
0.153728 |
0.116429 |
| 64 |
0.155492 |
0.123688 |
| 128 |
0.157941 |
0.127930 |
| 256 |
0.158279 |
0.129637 |
| 512 |
0.158191 |
0.130441 |
| 1024 |
0.158670 |
0.131255 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.188307 |
0.232762 |
| 4 |
0.184946 |
0.217448 |
| 8 |
0.177639 |
0.189640 |
| 16 |
0.169843 |
0.163382 |
| 32 |
0.164379 |
0.148306 |
| 64 |
0.161758 |
0.140040 |
| 128 |
0.160186 |
0.135648 |
| 256 |
0.159371 |
0.133623 |
| 512 |
0.158992 |
0.132738 |
| 1024 |
0.158849 |
0.132288 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.252933 |
0.306144 |
| 4 |
0.205438 |
0.244245 |
| 8 |
0.179973 |
0.194401 |
| 16 |
0.169839 |
0.163434 |
| 32 |
0.164467 |
0.147966 |
| 64 |
0.161755 |
0.139886 |
| 128 |
0.160254 |
0.135331 |
| 256 |
0.159717 |
0.133375 |
| 512 |
0.159192 |
0.132621 |
| 1024 |
0.158736 |
0.131926 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
0.112866 |
| THEORETICAL |
0.067929 |
| EMPIRICAL_TEST |
0.127094 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
0.075764 |
| 2 |
0.074668 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
0.038955 |
| 1 |
0.030226 |
| 2 |
0.020240 |
| 3 |
0.015282 |
| 4 |
0.010316 |
| 5 |
0.008099 |
| 6 |
0.007295 |
| 7 |
0.008762 |
| 8 |
0.015503 |
| 9 |
0.034915 |
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 |
22600 |
| 4 |
11440 |
16000 |
| 8 |
8008 |
5768 |
| 16 |
5240 |
5560 |
| 32 |
2828 |
3248 |
| 64 |
2160 |
2020 |
| 128 |
1806 |
1624 |
| 256 |
1010 |
1030 |
| 512 |
707 |
714 |
| 1024 |
515 |
505 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
22600 |
13899 |
| 4 |
14640 |
13520 |
| 8 |
8232 |
9408 |
| 16 |
6440 |
7160 |
| 32 |
3696 |
3724 |
| 64 |
2500 |
2280 |
| 128 |
1610 |
1470 |
| 256 |
1070 |
1050 |
| 512 |
1092 |
798 |
| 1024 |
640 |
540 |