Table 3.

Scalability with number of features ($d+1$).

Number of features ($d+1$)	Scikit-learn time (ms)	D-wave preprocessing time (ms)	D-wave annealing time (ms)	D-wave compute time (preprocess + anneal) (ms)	D-wave network overheads (ms)
2	20.6123 ± 1.2042	5.1378 ± 0.3802	12.5076 ± 0.0007	17.6454 ± 0.3802	706.1933 ± 84.0029
4	30.6010 ± 1.2382	13.7718 ± 0.9632	12.5247 ± 0.0009	26.2965 ± 0.9632	754.6531 ± 67.8583
6	46.8912 ± 1.6430	21.4310 ± 1.7784	12.5450 ± 0.0008	33.9759 ± 1.7783	756.5598 ± 66.0033
8	68.4019 ± 3.9914	28.9740 ± 2.0591	12.5659 ± 0.0006	41.5398 ± 2.0590	715.7661 ± 61.4712
10	93.9764 ± 1.7518	35.6321 ± 2.2202	12.5935 ± 0.0010	48.2257 ± 2.2203	761.3451 ± 60.9483
12	118.1701 ± 2.0026	42.5206 ± 2.6595	12.6092 ± 0.0012	55.1297 ± 2.6596	781.4883 ± 91.1495
14	145.6177 ± 1.8870	52.2676 ± 3.2121	12.6140 ± 0.0008	64.8816 ± 3.2120	844.3496 ± 107.1684
16	175.5792 ± 2.4876	60.6022 ± 3.7414	12.6195 ± 0.0010	73.2217 ± 3.7415	877.4846 ± 103.0307
18	213.1724 ± 2.7332	65.1949 ± 3.6451	12.6222 ± 0.0004	77.8170 ± 3.6451	791.8038 ± 105.9935
20	236.3750 ± 4.6308	74.9983 ± 3.9706	12.6212 ± 0.0004	87.6194 ± 3.9706	920.5470 ± 55.5933
22	257.6503 ± 5.2920	80.3314 ± 4.9133	12.6215 ± 0.0005	92.9529 ± 4.9133	779.6944 ± 90.0467
24	281.3093 ± 4.0617	83.6467 ± 3.6455	12.6211 ± 0.0007	96.2678 ± 3.6457	847.5243 ± 113.3988
26	313.2982 ± 3.7929	89.3653 ± 2.9930	12.6197 ± 0.0008	101.9850 ± 2.9931	804.1284 ± 91.5301
28	343.8831 ± 4.3417	98.9982 ± 4.5461	12.6174 ± 0.0010	111.6156 ± 4.5462	900.9338 ± 50.4548
30	379.3123 ± 4.7932	108.6154 ± 5.0667	12.6093 ± 0.0007	121.2247 ± 5.0667	1709.0392 ± 7766.58
32	360.5327 ± 9.4234	116.3282 ± 5.2455	12.5901 ± 0.0004	128.9182 ± 5.2455	706.8372 ± 73.4864

Significant values are in bold.