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

Loss vs log(n) 3 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

Iterations vs log(n) 3 features

N* Relationship Matrixes
N* theoretical
| dim |
1 feature(s) |
2 feature(s) |
3 feature(s) |
| 1 feature(s) |
NaN |
NaN |
NaN |
| 2 feature(s) |
NaN |
NaN |
NaN |
| 3 feature(s) |
NaN |
NaN |
NaN |
N* empirical test
| dim |
1 feature(s) |
2 feature(s) |
3 feature(s) |
| 1 feature(s) |
NaN |
NaN |
NaN |
| 2 feature(s) |
NaN |
NaN |
NaN |
| 3 feature(s) |
NaN |
NaN |
NaN |
Loss Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
3 feature(s) |
| 2 |
0.000022 |
0.000000 |
0.0 |
| 4 |
0.120250 |
0.029562 |
0.0 |
| 8 |
0.141987 |
0.047288 |
0.0 |
| 16 |
0.149805 |
0.059531 |
0.0 |
| 32 |
0.153482 |
0.067355 |
0.0 |
| 64 |
0.156242 |
0.072633 |
0.0 |
| 128 |
0.157559 |
0.075335 |
0.0 |
| 256 |
0.158164 |
0.077039 |
0.0 |
| 512 |
0.158682 |
0.077846 |
0.0 |
| 1024 |
0.158468 |
0.078187 |
0.0 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
3 feature(s) |
| 2 |
0.188072 |
0.150304 |
1.418542e-01 |
| 4 |
0.185036 |
0.139818 |
2.695884e-02 |
| 8 |
0.178260 |
0.120261 |
1.094526e-03 |
| 16 |
0.169652 |
0.101886 |
8.005068e-08 |
| 32 |
0.164467 |
0.091842 |
9.147119e-11 |
| 64 |
0.161676 |
0.085563 |
4.111123e-16 |
| 128 |
0.160179 |
0.082309 |
1.177747e-19 |
| 256 |
0.159397 |
0.080536 |
0.000000e+00 |
| 512 |
0.159000 |
0.079552 |
0.000000e+00 |
| 1024 |
0.158816 |
0.079123 |
0.000000e+00 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
3 feature(s) |
| 2 |
0.251634 |
0.172242 |
0.166531 |
| 4 |
0.207009 |
0.146707 |
0.027869 |
| 8 |
0.181406 |
0.121153 |
0.001089 |
| 16 |
0.169789 |
0.102043 |
0.000000 |
| 32 |
0.164450 |
0.091307 |
0.000000 |
| 64 |
0.161612 |
0.085361 |
0.000000 |
| 128 |
0.160166 |
0.082033 |
0.000000 |
| 256 |
0.159329 |
0.080300 |
0.000000 |
| 512 |
0.159052 |
0.079178 |
0.000000 |
| 1024 |
0.158797 |
0.078903 |
0.000000 |
Time Consumption Tables
Table EMPIRICAL_TRAIN
| loss type |
time (min) |
| EMPIRICAL_TRAIN |
0.112801 |
| THEORETICAL |
0.071445 |
| EMPIRICAL_TEST |
0.143405 |
Table THEORETICAL
| # features |
time (min) |
| 1 |
0.071777 |
| 2 |
0.059407 |
| 3 |
0.036089 |
Table EMPIRICAL_TEST
| n |
time (min) |
| 0 |
0.048262 |
| 1 |
0.036985 |
| 2 |
0.024136 |
| 3 |
0.016679 |
| 4 |
0.012836 |
| 5 |
0.009923 |
| 6 |
0.007273 |
| 7 |
0.008359 |
| 8 |
0.014196 |
| 9 |
0.029680 |
Iterations Tables
Table EMPIRICAL_TRAIN
| n |
1 feature(s) |
2 feature(s) |
3 feature(s) |
| 2 |
22600 |
11413 |
11413 |
| 4 |
16000 |
16000 |
8080 |
| 8 |
11200 |
11200 |
5656 |
| 16 |
8000 |
8000 |
4040 |
| 32 |
5600 |
5600 |
2828 |
| 64 |
4000 |
4000 |
2020 |
| 128 |
2800 |
1876 |
1414 |
| 256 |
2000 |
2000 |
1010 |
| 512 |
1400 |
1358 |
707 |
| 1024 |
1000 |
1000 |
505 |
Table THEORETICAL
| n |
1 feature(s) |
2 feature(s) |
3 feature(s) |
| 2 |
14464 |
16837 |
16385 |
| 4 |
12480 |
9280 |
10720 |
| 8 |
7280 |
9800 |
7112 |
| 16 |
4440 |
4080 |
4040 |
| 32 |
4256 |
3136 |
2828 |
| 64 |
2260 |
2420 |
2020 |
| 128 |
1540 |
1736 |
1414 |
| 256 |
1050 |
1050 |
1010 |
| 512 |
714 |
707 |
707 |
| 1024 |
505 |
515 |
505 |
Table EMPIRICAL_TEST
| n |
1 feature(s) |
2 feature(s) |
3 feature(s) |
| 2 |
16950 |
18984 |
17515 |
| 4 |
12080 |
16000 |
13600 |
| 8 |
6272 |
8008 |
7112 |
| 16 |
6800 |
5160 |
4040 |
| 32 |
5600 |
3976 |
2828 |
| 64 |
2020 |
4000 |
2020 |
| 128 |
1554 |
1610 |
1414 |
| 256 |
1030 |
1030 |
1010 |
| 512 |
938 |
749 |
707 |
| 1024 |
600 |
530 |
505 |