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 |
19.4728 |
| 2 feature(s) |
19.4728 |
NaN |
N* empirical test
| dim |
1 feature(s) |
2 feature(s) |
| 1 feature(s) |
NaN |
19.8219 |
| 2 feature(s) |
19.8219 |
NaN |
Loss Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.000000 |
0.000000 |
| 4 |
0.119922 |
0.057859 |
| 8 |
0.140089 |
0.095190 |
| 16 |
0.148602 |
0.114172 |
| 32 |
0.152757 |
0.124470 |
| 64 |
0.155484 |
0.130309 |
| 128 |
0.157506 |
0.134520 |
| 256 |
0.157512 |
0.135408 |
| 512 |
0.157852 |
0.136145 |
| 1024 |
0.158227 |
0.136814 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.187778 |
0.283266 |
| 4 |
0.185268 |
0.252571 |
| 8 |
0.177612 |
0.208030 |
| 16 |
0.169385 |
0.173435 |
| 32 |
0.164726 |
0.154485 |
| 64 |
0.161742 |
0.145894 |
| 128 |
0.160161 |
0.141455 |
| 256 |
0.159377 |
0.139429 |
| 512 |
0.159004 |
0.138443 |
| 1024 |
0.158855 |
0.138037 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
0.250600 |
0.424174 |
| 4 |
0.206744 |
0.301037 |
| 8 |
0.180016 |
0.216004 |
| 16 |
0.169326 |
0.173803 |
| 32 |
0.164565 |
0.154554 |
| 64 |
0.161503 |
0.145827 |
| 128 |
0.159944 |
0.141095 |
| 256 |
0.159028 |
0.139207 |
| 512 |
0.158716 |
0.138181 |
| 1024 |
0.158374 |
0.137600 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
7.517177 |
| THEORETICAL |
4.983536 |
| EMPIRICAL_TEST |
8.024653 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
4.342270 |
| 2 |
5.531474 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
2.142881 |
| 1 |
1.873799 |
| 2 |
1.220539 |
| 3 |
0.983917 |
| 4 |
0.655745 |
| 5 |
0.524865 |
| 6 |
0.524986 |
| 7 |
0.645186 |
| 8 |
1.079513 |
| 9 |
2.674360 |
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 |
2800 |
| 256 |
2000 |
2000 |
| 512 |
1400 |
1400 |
| 1024 |
1000 |
1000 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
| 2 |
11865 |
22600 |
| 4 |
16000 |
14400 |
| 8 |
6664 |
8456 |
| 16 |
4840 |
7880 |
| 32 |
2968 |
5572 |
| 64 |
2220 |
2700 |
| 128 |
1428 |
1414 |
| 256 |
1110 |
1040 |
| 512 |
714 |
714 |
| 1024 |
505 |
525 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
| 2 |
11752 |
15820 |
| 4 |
15120 |
16000 |
| 8 |
9352 |
6328 |
| 16 |
4840 |
7080 |
| 32 |
3360 |
3752 |
| 64 |
2620 |
2280 |
| 128 |
2380 |
1512 |
| 256 |
1170 |
1080 |
| 512 |
840 |
847 |
| 1024 |
540 |
640 |