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 |
NaN |
| 2 feature(s) |
NaN |
NaN |
N* empirical test
| dim |
1 feature(s) |
2 feature(s) |
| 1 feature(s) |
NaN |
NaN |
| 2 feature(s) |
NaN |
NaN |
Loss Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.000000 |
0.000000 |
| 4 |
0.118766 |
0.000234 |
| 8 |
0.139877 |
0.000379 |
| 16 |
0.148398 |
0.000500 |
| 32 |
0.153326 |
0.000552 |
| 64 |
0.156574 |
0.000629 |
| 128 |
0.157397 |
0.000558 |
| 256 |
0.157859 |
0.000680 |
| 512 |
0.158207 |
0.000645 |
| 1024 |
0.158408 |
0.000679 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.188015 |
0.087585 |
| 4 |
0.185337 |
0.028958 |
| 8 |
0.177584 |
0.010807 |
| 16 |
0.169547 |
0.004759 |
| 32 |
0.164365 |
0.002572 |
| 64 |
0.161685 |
0.001679 |
| 128 |
0.160081 |
0.001260 |
| 256 |
0.159388 |
0.001072 |
| 512 |
0.159016 |
0.000960 |
| 1024 |
0.158868 |
0.000903 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.252686 |
0.096043 |
| 4 |
0.204780 |
0.029321 |
| 8 |
0.181056 |
0.010751 |
| 16 |
0.169745 |
0.004764 |
| 32 |
0.164591 |
0.002578 |
| 64 |
0.161729 |
0.001664 |
| 128 |
0.160287 |
0.001241 |
| 256 |
0.159500 |
0.001043 |
| 512 |
0.159191 |
0.000926 |
| 1024 |
0.158764 |
0.000880 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
0.082737 |
| THEORETICAL |
0.053947 |
| EMPIRICAL_TEST |
0.099182 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
0.070329 |
| 2 |
0.045195 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
0.032381 |
| 1 |
0.025015 |
| 2 |
0.023651 |
| 3 |
0.012664 |
| 4 |
0.009538 |
| 5 |
0.007692 |
| 6 |
0.006095 |
| 7 |
0.006431 |
| 8 |
0.010096 |
| 9 |
0.019219 |
Iterations Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
11413 |
11413 |
| 4 |
16000 |
16000 |
| 8 |
11200 |
11200 |
| 16 |
8000 |
8000 |
| 32 |
5600 |
5600 |
| 64 |
4000 |
4000 |
| 128 |
2800 |
1638 |
| 256 |
2000 |
2000 |
| 512 |
1400 |
1400 |
| 1024 |
1000 |
1000 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
13560 |
21018 |
| 4 |
9600 |
16000 |
| 8 |
8400 |
7448 |
| 16 |
4120 |
4200 |
| 32 |
3164 |
2940 |
| 64 |
2240 |
2140 |
| 128 |
1414 |
1414 |
| 256 |
1080 |
1010 |
| 512 |
707 |
707 |
| 1024 |
510 |
505 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
19549 |
17967 |
| 4 |
9120 |
11360 |
| 8 |
11200 |
9128 |
| 16 |
4040 |
4200 |
| 32 |
3248 |
2884 |
| 64 |
2400 |
2120 |
| 128 |
1988 |
1442 |
| 256 |
1100 |
1030 |
| 512 |
1029 |
756 |
| 1024 |
555 |
510 |