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dmeoli committed Mar 28, 2021
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2,272 changes: 1,137 additions & 1,135 deletions notebooks/ml/CM_SVC_report_experiments.ipynb
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4,421 changes: 1,199 additions & 3,222 deletions notebooks/ml/CM_SVR_report_experiments.ipynb
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18 changes: 9 additions & 9 deletions notebooks/ml/tex/experiments/linear_dual_svc.tex
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& & fit\_time & n\_iter & train\_accuracy & val\_accuracy & train\_n\_sv & val\_n\_sv \\
solver & C & & & & & & \\
\midrule
smo & 1 & 0.054521 & 41 & 0.967493 & 0.969998 & 15 & 15 \\
& 10 & 0.178687 & 216 & 0.967493 & 0.964948 & 12 & 12 \\
& 100 & 0.463555 & 1039 & 0.967493 & 0.964948 & 11 & 11 \\
libsvm & 1 & 0.001915 & 58 & 0.969981 & 0.964948 & 15 & 15 \\
& 10 & 0.003209 & 728 & 0.969981 & 0.964948 & 12 & 12 \\
& 100 & 0.004323 & 4114 & 0.967493 & 0.964948 & 11 & 11 \\
cvxopt & 1 & 0.032567 & 10 & 0.967493 & 0.969998 & 15 & 15 \\
& 10 & 0.020921 & 10 & 0.967493 & 0.969998 & 14 & 14 \\
& 100 & 0.043281 & 10 & 0.967493 & 0.964948 & 24 & 24 \\
smo & 1 & 0.076588 & 61 & 0.985000 & 0.989974 & 12 & 12 \\
& 10 & 0.076181 & 73 & 0.985000 & 0.979949 & 7 & 7 \\
& 100 & 0.373685 & 1196 & 0.985000 & 0.989974 & 6 & 6 \\
libsvm & 1 & 0.003042 & 99 & 0.987487 & 0.989974 & 12 & 12 \\
& 10 & 0.002565 & 90 & 0.987487 & 0.984999 & 7 & 7 \\
& 100 & 0.003477 & 2647 & 0.985000 & 0.984999 & 6 & 6 \\
cvxopt & 1 & 0.020731 & 10 & 0.985000 & 0.989974 & 12 & 12 \\
& 10 & 0.016735 & 10 & 0.985000 & 0.989974 & 7 & 7 \\
& 100 & 0.029245 & 10 & 0.985000 & 0.989974 & 8 & 8 \\
\bottomrule
\end{tabular}
\end{table}
54 changes: 27 additions & 27 deletions notebooks/ml/tex/experiments/linear_dual_svr.tex
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& & & fit\_time & n\_iter & train\_r2 & val\_r2 & train\_n\_sv & val\_n\_sv \\
solver & C & epsilon & & & & & & \\
\midrule
smo & 10 & 0.2 & 0.041816 & 30 & 0.839199 & 0.824149 & 67 & 67 \\
& 100 & 0.3 & 0.231624 & 136 & 0.838683 & 0.821843 & 66 & 66 \\
& & 0.1 & 0.161679 & 128 & 0.838229 & 0.820990 & 66 & 66 \\
& 10 & 0.3 & 0.037710 & 35 & 0.839234 & 0.824092 & 67 & 67 \\
& & 0.1 & 0.039658 & 30 & 0.839160 & 0.824200 & 67 & 67 \\
& 1 & 0.3 & 0.015873 & 12 & 0.816829 & 0.806018 & 66 & 66 \\
& & 0.2 & 0.016650 & 13 & 0.816266 & 0.805431 & 66 & 66 \\
& & 0.1 & 0.018286 & 13 & 0.815865 & 0.804998 & 66 & 66 \\
& 100 & 0.2 & 0.206949 & 185 & 0.838469 & 0.821431 & 66 & 66 \\
libsvm & 1 & 0.3 & 0.003237 & 57 & 0.816092 & 0.803425 & 66 & 66 \\
& 10 & 0.1 & 0.003931 & 111 & 0.837101 & 0.825608 & 67 & 67 \\
& & 0.2 & 0.001921 & 114 & 0.837315 & 0.825348 & 67 & 67 \\
& & 0.3 & 0.001678 & 163 & 0.837508 & 0.825064 & 67 & 67 \\
& 1 & 0.1 & 0.003243 & 52 & 0.815113 & 0.803346 & 66 & 66 \\
& 100 & 0.1 & 0.002190 & 1081 & 0.836676 & 0.824330 & 66 & 66 \\
& & 0.2 & 0.001872 & 762 & 0.836958 & 0.824744 & 66 & 66 \\
& 1 & 0.2 & 0.005966 & 52 & 0.815554 & 0.803517 & 66 & 66 \\
& 100 & 0.3 & 0.001949 & 1433 & 0.837205 & 0.825121 & 66 & 66 \\
cvxopt & 1 & 0.2 & 0.018971 & 10 & 0.816274 & 0.805607 & 66 & 66 \\
& 100 & 0.3 & 0.010127 & 8 & 0.838686 & 0.822088 & 67 & 67 \\
& & 0.2 & 0.014582 & 8 & 0.838473 & 0.821675 & 67 & 67 \\
& & 0.1 & 0.012519 & 8 & 0.838233 & 0.821232 & 67 & 67 \\
& 10 & 0.3 & 0.013504 & 8 & 0.839237 & 0.824234 & 67 & 67 \\
& & 0.2 & 0.013448 & 8 & 0.839203 & 0.824285 & 67 & 67 \\
& & 0.1 & 0.016795 & 8 & 0.839164 & 0.824329 & 67 & 67 \\
& 1 & 0.3 & 0.012157 & 9 & 0.816837 & 0.806148 & 67 & 67 \\
& & 0.1 & 0.021911 & 9 & 0.815872 & 0.805162 & 67 & 67 \\
smo & 10 & 0.2 & 0.139534 & 219 & 0.977926 & 0.972457 & 65 & 65 \\
& 100 & 0.3 & 0.383196 & 900 & 0.977737 & 0.973939 & 66 & 66 \\
& & 0.1 & 0.524643 & 1508 & 0.977788 & 0.974139 & 66 & 66 \\
& 10 & 0.3 & 0.053870 & 38 & 0.977953 & 0.972544 & 65 & 65 \\
& & 0.1 & 0.053832 & 56 & 0.977920 & 0.972445 & 66 & 66 \\
& 1 & 0.3 & 0.039421 & 60 & 0.918942 & 0.915576 & 66 & 66 \\
& & 0.2 & 0.022597 & 13 & 0.918341 & 0.915019 & 66 & 66 \\
& & 0.1 & 0.017338 & 15 & 0.917773 & 0.914442 & 66 & 66 \\
& 100 & 0.2 & 0.266404 & 394 & 0.977742 & 0.974022 & 66 & 66 \\
libsvm & 1 & 0.3 & 0.002088 & 54 & 0.918786 & 0.916554 & 66 & 66 \\
& 10 & 0.1 & 0.001896 & 282 & 0.977852 & 0.972051 & 66 & 66 \\
& & 0.2 & 0.001990 & 193 & 0.977851 & 0.972025 & 65 & 65 \\
& & 0.3 & 0.001814 & 593 & 0.977870 & 0.972135 & 65 & 65 \\
& 1 & 0.1 & 0.003532 & 63 & 0.917627 & 0.915448 & 66 & 66 \\
& 100 & 0.1 & 0.003821 & 2621 & 0.977723 & 0.974270 & 66 & 66 \\
& & 0.2 & 0.003551 & 2709 & 0.977673 & 0.974122 & 66 & 66 \\
& 1 & 0.2 & 0.003926 & 102 & 0.918194 & 0.915985 & 66 & 66 \\
& 100 & 0.3 & 0.003090 & 4141 & 0.977655 & 0.974045 & 66 & 66 \\
cvxopt & 1 & 0.2 & 0.017439 & 9 & 0.918341 & 0.915058 & 67 & 67 \\
& 100 & 0.3 & 0.021550 & 9 & 0.977737 & 0.973956 & 67 & 67 \\
& & 0.2 & 0.024708 & 9 & 0.977742 & 0.974033 & 67 & 67 \\
& & 0.1 & 0.020310 & 9 & 0.977788 & 0.974150 & 67 & 67 \\
& 10 & 0.3 & 0.025372 & 10 & 0.977954 & 0.972562 & 66 & 66 \\
& & 0.2 & 0.018264 & 9 & 0.977926 & 0.972474 & 67 & 67 \\
& & 0.1 & 0.024514 & 9 & 0.977920 & 0.972466 & 67 & 67 \\
& 1 & 0.3 & 0.013357 & 10 & 0.918942 & 0.915614 & 66 & 66 \\
& & 0.1 & 0.017656 & 9 & 0.917772 & 0.914479 & 67 & 67 \\
\bottomrule
\end{tabular}
\end{table}
12 changes: 6 additions & 6 deletions notebooks/ml/tex/experiments/linear_lagrangian_dual_svc.tex
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& & fit\_time & n\_iter & train\_accuracy & val\_accuracy & train\_n\_sv & val\_n\_sv \\
dual & C & & & & & & \\
\midrule
qp & 1 & 0.009340 & 1 & 0.977518 & 0.980024 & 130 & 130 \\
& 10 & 0.005536 & 1 & 0.977518 & 0.980024 & 130 & 130 \\
& 100 & 0.006986 & 1 & 0.977518 & 0.980024 & 130 & 130 \\
bcqp & 1 & 0.006575 & 1 & 0.964987 & 0.980024 & 129 & 129 \\
& 10 & 0.005960 & 1 & 0.964987 & 0.980024 & 129 & 129 \\
& 100 & 0.004786 & 1 & 0.964987 & 0.980024 & 129 & 129 \\
qp & 1 & 0.006492 & 1 & 0.985019 & 0.989974 & 131 & 131 \\
& 10 & 0.006105 & 1 & 0.985019 & 0.989974 & 131 & 131 \\
& 100 & 0.005686 & 1 & 0.985019 & 0.989974 & 131 & 131 \\
bcqp & 1 & 0.006973 & 1 & 0.985019 & 0.989974 & 130 & 130 \\
& 10 & 0.006043 & 1 & 0.985019 & 0.989974 & 130 & 130 \\
& 100 & 0.005027 & 1 & 0.985019 & 0.989974 & 130 & 130 \\
\bottomrule
\end{tabular}
\end{table}
36 changes: 18 additions & 18 deletions notebooks/ml/tex/experiments/linear_lagrangian_dual_svr.tex
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& & & fit\_time & n\_iter & train\_r2 & val\_r2 & train\_n\_sv & val\_n\_sv \\
dual & C & epsilon & & & & & & \\
\midrule
qp & 1 & 0.1 & 0.082322 & 44 & 0.684957 & 0.676764 & 67 & 67 \\
& & 0.2 & 0.087632 & 44 & 0.684957 & 0.676764 & 67 & 67 \\
& & 0.3 & 0.083518 & 44 & 0.684957 & 0.676763 & 67 & 67 \\
& 10 & 0.1 & 0.823205 & 728 & 0.736303 & 0.730094 & 67 & 67 \\
& & 0.2 & 0.840446 & 735 & 0.736303 & 0.730093 & 67 & 67 \\
& & 0.3 & 0.794968 & 741 & 0.736303 & 0.730092 & 67 & 67 \\
& 100 & 0.1 & 0.870177 & 728 & 0.736303 & 0.730094 & 67 & 67 \\
& & 0.2 & 0.520331 & 735 & 0.736303 & 0.730093 & 67 & 67 \\
& & 0.3 & 0.570781 & 741 & 0.736303 & 0.730092 & 67 & 67 \\
bcqp & 1 & 0.1 & 0.050349 & 32 & 0.683134 & 0.674912 & 67 & 67 \\
& & 0.2 & 0.051552 & 32 & 0.683134 & 0.674912 & 67 & 67 \\
& & 0.3 & 0.053362 & 32 & 0.683134 & 0.674911 & 67 & 67 \\
& 10 & 0.1 & 0.242091 & 207 & 0.738281 & 0.732098 & 67 & 67 \\
& & 0.2 & 0.229870 & 209 & 0.738281 & 0.732097 & 67 & 67 \\
& & 0.3 & 0.245216 & 210 & 0.738281 & 0.732096 & 67 & 67 \\
& 100 & 0.1 & 0.243215 & 207 & 0.738281 & 0.732098 & 67 & 67 \\
& & 0.2 & 0.113374 & 209 & 0.738281 & 0.732097 & 67 & 67 \\
& & 0.3 & 0.186780 & 210 & 0.738281 & 0.732096 & 67 & 67 \\
qp & 1 & 0.1 & 0.711464 & 653 & 0.876534 & 0.870926 & 67 & 67 \\
& & 0.2 & 0.820021 & 653 & 0.876534 & 0.870927 & 67 & 67 \\
& & 0.3 & 0.648664 & 653 & 0.876534 & 0.870927 & 67 & 67 \\
& 10 & 0.1 & 0.510787 & 519 & 0.731825 & 0.722021 & 67 & 67 \\
& & 0.2 & 0.558384 & 524 & 0.731825 & 0.722021 & 67 & 67 \\
& & 0.3 & 0.519468 & 530 & 0.731825 & 0.722020 & 67 & 67 \\
& 100 & 0.1 & 0.631134 & 519 & 0.731825 & 0.722021 & 67 & 67 \\
& & 0.2 & 0.520121 & 524 & 0.731825 & 0.722021 & 67 & 67 \\
& & 0.3 & 0.539273 & 530 & 0.731825 & 0.722020 & 67 & 67 \\
bcqp & 1 & 0.1 & 0.630620 & 522 & 0.731073 & 0.721200 & 67 & 67 \\
& & 0.2 & 0.639167 & 524 & 0.731073 & 0.721199 & 67 & 67 \\
& & 0.3 & 0.630822 & 526 & 0.731073 & 0.721199 & 67 & 67 \\
& 10 & 0.1 & 0.610205 & 539 & 0.733638 & 0.723925 & 67 & 67 \\
& & 0.2 & 0.657547 & 541 & 0.733638 & 0.723924 & 67 & 67 \\
& & 0.3 & 0.637749 & 543 & 0.733638 & 0.723924 & 67 & 67 \\
& 100 & 0.1 & 0.635853 & 539 & 0.733638 & 0.723925 & 67 & 67 \\
& & 0.2 & 0.527298 & 541 & 0.733638 & 0.723924 & 67 & 67 \\
& & 0.3 & 0.494042 & 543 & 0.733638 & 0.723924 & 67 & 67 \\
\bottomrule
\end{tabular}
\end{table}
36 changes: 18 additions & 18 deletions notebooks/ml/tex/experiments/nonlinear_dual_svc.tex
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& & & fit\_time & n\_iter & train\_accuracy & val\_accuracy & train\_n\_sv & val\_n\_sv \\
solver & kernel & C & & & & & & \\
\midrule
smo & poly & 1 & 0.300656 & 94 & 0.816287 & 0.708488 & 32 & 32 \\
& & 10 & 0.304991 & 108 & 0.926131 & 0.743650 & 10 & 10 \\
& & 100 & 0.265495 & 172 & 0.957426 & 0.828302 & 8 & 8 \\
& rbf & 1 & 0.253971 & 50 & 0.998747 & 1.000000 & 43 & 43 \\
& & 10 & 0.275428 & 93 & 1.000000 & 1.000000 & 14 & 14 \\
& & 100 & 0.220114 & 81 & 1.000000 & 1.000000 & 11 & 11 \\
libsvm & poly & 1 & 0.003757 & 270 & 0.998747 & 0.992481 & 32 & 32 \\
& & 10 & 0.003405 & 319 & 1.000000 & 0.992481 & 10 & 10 \\
& & 100 & 0.003105 & 274 & 1.000000 & 0.992481 & 8 & 8 \\
& rbf & 1 & 0.003656 & 99 & 1.000000 & 1.000000 & 44 & 44 \\
& & 10 & 0.004566 & 149 & 1.000000 & 1.000000 & 14 & 14 \\
& & 100 & 0.003053 & 205 & 1.000000 & 1.000000 & 11 & 11 \\
cvxopt & poly & 1 & 0.085239 & 10 & 0.815039 & 0.705981 & 32 & 32 \\
& & 10 & 0.074714 & 10 & 0.926131 & 0.743650 & 10 & 10 \\
& & 100 & 0.066410 & 10 & 0.957426 & 0.828302 & 9 & 9 \\
& rbf & 1 & 0.096586 & 10 & 0.998747 & 1.000000 & 44 & 44 \\
& & 10 & 0.082683 & 10 & 1.000000 & 1.000000 & 15 & 15 \\
& & 100 & 0.073029 & 10 & 1.000000 & 1.000000 & 14 & 14 \\
smo & poly & 1 & 0.356696 & 88 & 0.851206 & 0.678412 & 28 & 28 \\
& & 10 & 0.270690 & 105 & 0.897426 & 0.660682 & 9 & 9 \\
& & 100 & 0.255688 & 198 & 0.916209 & 0.727921 & 8 & 8 \\
& rbf & 1 & 0.245166 & 49 & 1.000000 & 1.000000 & 41 & 41 \\
& & 10 & 0.204894 & 52 & 1.000000 & 1.000000 & 13 & 13 \\
& & 100 & 0.188844 & 64 & 1.000000 & 1.000000 & 11 & 11 \\
libsvm & poly & 1 & 0.005154 & 160 & 1.000000 & 0.992481 & 28 & 28 \\
& & 10 & 0.004598 & 436 & 1.000000 & 0.987469 & 10 & 10 \\
& & 100 & 0.006573 & 149 & 1.000000 & 0.987469 & 8 & 8 \\
& rbf & 1 & 0.004991 & 115 & 1.000000 & 1.000000 & 41 & 41 \\
& & 10 & 0.002472 & 164 & 1.000000 & 1.000000 & 13 & 13 \\
& & 100 & 0.003032 & 268 & 1.000000 & 1.000000 & 12 & 12 \\
cvxopt & poly & 1 & 0.105617 & 10 & 0.851206 & 0.678412 & 28 & 28 \\
& & 10 & 0.095708 & 10 & 0.911206 & 0.688026 & 10 & 10 \\
& & 100 & 0.072921 & 10 & 0.916209 & 0.722889 & 9 & 9 \\
& rbf & 1 & 0.093452 & 10 & 1.000000 & 1.000000 & 43 & 43 \\
& & 10 & 0.073576 & 10 & 1.000000 & 1.000000 & 14 & 14 \\
& & 100 & 0.069153 & 10 & 1.000000 & 1.000000 & 13 & 13 \\
\bottomrule
\end{tabular}
\end{table}
24 changes: 12 additions & 12 deletions notebooks/ml/tex/experiments/nonlinear_lagrangian_dual_svc.tex
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& & & fit\_time & n\_iter & train\_accuracy & val\_accuracy & train\_n\_sv & val\_n\_sv \\
dual & kernel & C & & & & & & \\
\midrule
qp & poly & 1 & 0.635557 & 126 & 0.774971 & 0.521266 & 205 & 205 \\
& & 10 & 0.579004 & 121 & 0.782462 & 0.533797 & 205 & 205 \\
& & 100 & 0.612130 & 121 & 0.782462 & 0.533797 & 205 & 205 \\
& rbf & 1 & 1.728111 & 269 & 0.758741 & 0.501253 & 136 & 136 \\
& & 10 & 0.553077 & 82 & 0.750002 & 0.501253 & 109 & 109 \\
& & 100 & 1.160888 & 359 & 0.831151 & 0.578947 & 149 & 149 \\
bcqp & poly & 1 & 1.149153 & 347 & 0.784959 & 0.543785 & 206 & 206 \\
& & 10 & 0.986511 & 347 & 0.784959 & 0.543785 & 206 & 206 \\
& & 100 & 0.718925 & 347 & 0.784959 & 0.543785 & 206 & 206 \\
& rbf & 1 & 0.022847 & 1 & 0.998747 & 0.992519 & 249 & 249 \\
& & 10 & 0.020183 & 1 & 0.998747 & 0.992519 & 249 & 249 \\
& & 100 & 0.020089 & 1 & 0.998747 & 0.992519 & 249 & 249 \\
qp & poly & 1 & 1.315738 & 255 & 0.733773 & 0.513784 & 184 & 184 \\
& & 10 & 1.178677 & 255 & 0.733773 & 0.513784 & 184 & 184 \\
& & 100 & 1.203893 & 255 & 0.733773 & 0.513784 & 184 & 184 \\
& rbf & 1 & 1.241991 & 229 & 0.822618 & 0.727734 & 186 & 186 \\
& & 10 & 1.696262 & 376 & 0.751255 & 0.503741 & 153 & 153 \\
& & 100 & 1.312007 & 305 & 0.833652 & 0.586447 & 178 & 178 \\
bcqp & poly & 1 & 1.480641 & 337 & 0.783729 & 0.538810 & 199 & 199 \\
& & 10 & 1.266989 & 337 & 0.783729 & 0.538810 & 199 & 199 \\
& & 100 & 1.023042 & 337 & 0.783729 & 0.538810 & 199 & 199 \\
& rbf & 1 & 0.020001 & 1 & 0.998747 & 0.982568 & 240 & 240 \\
& & 10 & 0.021672 & 1 & 0.998747 & 0.982568 & 240 & 240 \\
& & 100 & 0.023396 & 1 & 0.998747 & 0.982568 & 240 & 240 \\
\bottomrule
\end{tabular}
\end{table}

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