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@@ -1,15 +1,15 @@ | ||
\begin{tabular}{llrrrrr} | ||
\toprule | ||
optimizer & C & fit\_time & train\_accuracy & test\_accuracy & nr\_train\_sv & nr\_test\_sv \\ | ||
solver & C & fit\_time & train\_accuracy & val\_accuracy & nr\_train\_sv & nr\_val\_sv \\ | ||
\midrule | ||
cvxopt & 1 & 0.046403 & 0.990012 & 0.990050 & 12 & 12 \\ | ||
libsvm & 1 & 0.004200 & 0.990012 & 0.990050 & 26 & 26 \\ | ||
smo & 1 & 0.071781 & 0.990012 & 0.990050 & 12 & 12 \\ | ||
cvxopt & 10 & 0.025000 & 0.992519 & 0.980100 & 7 & 7 \\ | ||
libsvm & 10 & 0.004469 & 0.997512 & 0.990050 & 13 & 13 \\ | ||
smo & 10 & 0.085767 & 0.992519 & 0.980100 & 7 & 7 \\ | ||
cvxopt & 100 & 0.020040 & 0.992519 & 0.980100 & 6 & 6 \\ | ||
libsvm & 100 & 0.003470 & 0.997512 & 0.985075 & 10 & 10 \\ | ||
smo & 100 & 0.121755 & 0.992519 & 0.980100 & 6 & 6 \\ | ||
cvxopt & 1 & 0.063277 & 0.985019 & 0.980100 & 11 & 11 \\ | ||
libsvm & 1 & 0.003978 & 0.980025 & 0.969998 & 13 & 13 \\ | ||
smo & 1 & 0.194799 & 0.985019 & 0.980100 & 11 & 11 \\ | ||
cvxopt & 10 & 0.050291 & 0.987506 & 0.980100 & 7 & 7 \\ | ||
libsvm & 10 & 0.004888 & 0.980006 & 0.974974 & 9 & 9 \\ | ||
smo & 10 & 0.243180 & 0.987506 & 0.975049 & 6 & 6 \\ | ||
cvxopt & 100 & 0.023014 & 0.990012 & 0.980100 & 6 & 6 \\ | ||
libsvm & 100 & 0.006158 & 0.980006 & 0.969998 & 8 & 8 \\ | ||
smo & 100 & 0.600229 & 0.985000 & 0.975049 & 6 & 6 \\ | ||
\bottomrule | ||
\end{tabular} |
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@@ -1,33 +1,33 @@ | ||
\begin{tabular}{lllrrrrr} | ||
\toprule | ||
optimizer & C & epsilon & fit\_time & train\_r2 & test\_r2 & nr\_train\_sv & nr\_test\_sv \\ | ||
solver & C & epsilon & fit\_time & train\_r2 & val\_r2 & nr\_train\_sv & nr\_val\_sv \\ | ||
\midrule | ||
cvxopt & 1 & 0.1 & 0.016043 & 0.917772 & 0.914479 & 67 & 67 \\ | ||
cvxopt & 1 & 0.2 & 0.013932 & 0.918341 & 0.915058 & 67 & 67 \\ | ||
cvxopt & 1 & 0.3 & 0.013713 & 0.918942 & 0.915614 & 66 & 66 \\ | ||
libsvm & 1 & 0.1 & 0.001461 & 0.301059 & 0.267819 & 66 & 66 \\ | ||
libsvm & 1 & 0.2 & 0.001329 & 0.301044 & 0.267620 & 66 & 66 \\ | ||
libsvm & 1 & 0.3 & 0.001335 & 0.301096 & 0.267529 & 66 & 66 \\ | ||
smo & 1 & 0.1 & 0.015769 & 0.917773 & 0.914442 & 66 & 66 \\ | ||
smo & 1 & 0.2 & 0.014345 & 0.918341 & 0.915019 & 66 & 66 \\ | ||
smo & 1 & 0.3 & 0.036733 & 0.918942 & 0.915576 & 66 & 66 \\ | ||
cvxopt & 10 & 0.1 & 0.011870 & 0.977920 & 0.972466 & 67 & 67 \\ | ||
cvxopt & 10 & 0.2 & 0.011431 & 0.977926 & 0.972474 & 67 & 67 \\ | ||
cvxopt & 10 & 0.3 & 0.010734 & 0.977954 & 0.972562 & 66 & 66 \\ | ||
libsvm & 10 & 0.1 & 0.001118 & 0.854129 & 0.822864 & 66 & 66 \\ | ||
libsvm & 10 & 0.2 & 0.001050 & 0.854232 & 0.822988 & 66 & 66 \\ | ||
libsvm & 10 & 0.3 & 0.001065 & 0.854309 & 0.823114 & 65 & 65 \\ | ||
smo & 10 & 0.1 & 0.066876 & 0.977920 & 0.972445 & 66 & 66 \\ | ||
smo & 10 & 0.2 & 0.132380 & 0.977926 & 0.972457 & 65 & 65 \\ | ||
smo & 10 & 0.3 & 0.056308 & 0.977953 & 0.972544 & 65 & 65 \\ | ||
cvxopt & 100 & 0.1 & 0.010851 & 0.977788 & 0.974150 & 67 & 67 \\ | ||
cvxopt & 100 & 0.2 & 0.009956 & 0.977742 & 0.974033 & 67 & 67 \\ | ||
cvxopt & 100 & 0.3 & 0.010245 & 0.977737 & 0.973956 & 67 & 67 \\ | ||
libsvm & 100 & 0.1 & 0.001248 & 0.972911 & 0.957216 & 66 & 66 \\ | ||
libsvm & 100 & 0.2 & 0.001488 & 0.972980 & 0.957519 & 66 & 66 \\ | ||
libsvm & 100 & 0.3 & 0.001417 & 0.973084 & 0.957948 & 65 & 65 \\ | ||
smo & 100 & 0.1 & 0.503398 & 0.977788 & 0.974139 & 66 & 66 \\ | ||
smo & 100 & 0.2 & 0.232309 & 0.977742 & 0.974022 & 66 & 66 \\ | ||
smo & 100 & 0.3 & 0.464860 & 0.977737 & 0.973939 & 66 & 66 \\ | ||
cvxopt & 1 & 0.1 & 0.078818 & 0.917772 & 0.914479 & 67 & 67 \\ | ||
cvxopt & 1 & 0.2 & 0.083481 & 0.918341 & 0.915058 & 67 & 67 \\ | ||
cvxopt & 1 & 0.3 & 0.072449 & 0.918942 & 0.915614 & 66 & 66 \\ | ||
libsvm & 1 & 0.1 & 0.001410 & 0.917627 & 0.915448 & 66 & 66 \\ | ||
libsvm & 1 & 0.2 & 0.000902 & 0.918194 & 0.915985 & 66 & 66 \\ | ||
libsvm & 1 & 0.3 & 0.001214 & 0.918786 & 0.916554 & 66 & 66 \\ | ||
smo & 1 & 0.1 & 0.062739 & 0.917773 & 0.914442 & 66 & 66 \\ | ||
smo & 1 & 0.2 & 0.070250 & 0.918341 & 0.915019 & 66 & 66 \\ | ||
smo & 1 & 0.3 & 0.090543 & 0.918942 & 0.915576 & 66 & 66 \\ | ||
cvxopt & 10 & 0.1 & 0.028650 & 0.977920 & 0.972466 & 67 & 67 \\ | ||
cvxopt & 10 & 0.2 & 0.022306 & 0.977926 & 0.972474 & 67 & 67 \\ | ||
cvxopt & 10 & 0.3 & 0.013097 & 0.977954 & 0.972562 & 66 & 66 \\ | ||
libsvm & 10 & 0.1 & 0.001434 & 0.977852 & 0.972051 & 66 & 66 \\ | ||
libsvm & 10 & 0.2 & 0.001295 & 0.977851 & 0.972025 & 65 & 65 \\ | ||
libsvm & 10 & 0.3 & 0.001567 & 0.977870 & 0.972135 & 65 & 65 \\ | ||
smo & 10 & 0.1 & 0.117902 & 0.977920 & 0.972445 & 66 & 66 \\ | ||
smo & 10 & 0.2 & 0.185026 & 0.977926 & 0.972457 & 65 & 65 \\ | ||
smo & 10 & 0.3 & 0.069342 & 0.977953 & 0.972544 & 65 & 65 \\ | ||
cvxopt & 100 & 0.1 & 0.014835 & 0.977788 & 0.974150 & 67 & 67 \\ | ||
cvxopt & 100 & 0.2 & 0.014931 & 0.977742 & 0.974033 & 67 & 67 \\ | ||
cvxopt & 100 & 0.3 & 0.012269 & 0.977737 & 0.973956 & 67 & 67 \\ | ||
libsvm & 100 & 0.1 & 0.002421 & 0.977723 & 0.974270 & 66 & 66 \\ | ||
libsvm & 100 & 0.2 & 0.002740 & 0.977673 & 0.974122 & 66 & 66 \\ | ||
libsvm & 100 & 0.3 & 0.002715 & 0.977655 & 0.974045 & 66 & 66 \\ | ||
smo & 100 & 0.1 & 0.612424 & 0.977788 & 0.974139 & 66 & 66 \\ | ||
smo & 100 & 0.2 & 0.342281 & 0.977742 & 0.974022 & 66 & 66 \\ | ||
smo & 100 & 0.3 & 0.487434 & 0.977737 & 0.973939 & 66 & 66 \\ | ||
\bottomrule | ||
\end{tabular} |
14 changes: 7 additions & 7 deletions
14
notebooks/ml/tex/experiments/linear_lagrangian_dual_svc.tex
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@@ -1,12 +1,12 @@ | ||
\begin{tabular}{llrrrrr} | ||
\toprule | ||
ld & C & fit\_time & train\_accuracy & test\_accuracy & nr\_train\_sv & nr\_test\_sv \\ | ||
ld & C & fit\_time & train\_accuracy & val\_accuracy & nr\_train\_sv & nr\_val\_sv \\ | ||
\midrule | ||
bcqp & 1 & 0.017351 & 0.982512 & 0.990050 & 130 & 130 \\ | ||
qp & 1 & 0.013105 & 0.967512 & 0.965023 & 129 & 129 \\ | ||
bcqp & 10 & 0.005850 & 0.982512 & 0.990050 & 130 & 130 \\ | ||
qp & 10 & 0.010758 & 0.967512 & 0.965023 & 129 & 129 \\ | ||
bcqp & 100 & 0.013462 & 0.982512 & 0.990050 & 130 & 130 \\ | ||
qp & 100 & 0.007632 & 0.967512 & 0.965023 & 129 & 129 \\ | ||
bcqp & 1 & 0.018653 & 0.992481 & 0.994949 & 127 & 127 \\ | ||
qp & 1 & 0.013991 & 0.974993 & 0.980024 & 131 & 131 \\ | ||
bcqp & 10 & 0.018454 & 0.992481 & 0.994949 & 127 & 127 \\ | ||
qp & 10 & 0.013773 & 0.974993 & 0.980024 & 131 & 131 \\ | ||
bcqp & 100 & 0.018384 & 0.992481 & 0.994949 & 127 & 127 \\ | ||
qp & 100 & 0.016275 & 0.974993 & 0.980024 & 131 & 131 \\ | ||
\bottomrule | ||
\end{tabular} |
38 changes: 19 additions & 19 deletions
38
notebooks/ml/tex/experiments/linear_lagrangian_dual_svr.tex
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@@ -1,24 +1,24 @@ | ||
\begin{tabular}{lllrrrrr} | ||
\toprule | ||
ld & C & epsilon & fit\_time & train\_r2 & test\_r2 & nr\_train\_sv & nr\_test\_sv \\ | ||
ld & C & epsilon & fit\_time & train\_r2 & val\_r2 & nr\_train\_sv & nr\_val\_sv \\ | ||
\midrule | ||
bcqp & 1 & 0.1 & 0.668861 & 0.731073 & 0.721200 & 67 & 67 \\ | ||
bcqp & 1 & 0.2 & 0.691504 & 0.731073 & 0.721199 & 67 & 67 \\ | ||
bcqp & 1 & 0.3 & 0.596748 & 0.731073 & 0.721199 & 67 & 67 \\ | ||
qp & 1 & 0.1 & 0.690563 & 0.876534 & 0.870926 & 67 & 67 \\ | ||
qp & 1 & 0.2 & 0.701201 & 0.876534 & 0.870927 & 67 & 67 \\ | ||
qp & 1 & 0.3 & 0.763102 & 0.876534 & 0.870927 & 67 & 67 \\ | ||
bcqp & 10 & 0.1 & 0.695531 & 0.733638 & 0.723925 & 67 & 67 \\ | ||
bcqp & 10 & 0.2 & 0.632475 & 0.733638 & 0.723924 & 67 & 67 \\ | ||
bcqp & 10 & 0.3 & 0.641617 & 0.733638 & 0.723924 & 67 & 67 \\ | ||
qp & 10 & 0.1 & 0.511339 & 0.731825 & 0.722021 & 67 & 67 \\ | ||
qp & 10 & 0.2 & 0.527950 & 0.731825 & 0.722021 & 67 & 67 \\ | ||
qp & 10 & 0.3 & 0.532688 & 0.731825 & 0.722020 & 67 & 67 \\ | ||
bcqp & 100 & 0.1 & 0.533398 & 0.733638 & 0.723925 & 67 & 67 \\ | ||
bcqp & 100 & 0.2 & 0.518986 & 0.733638 & 0.723924 & 67 & 67 \\ | ||
bcqp & 100 & 0.3 & 0.472809 & 0.733638 & 0.723924 & 67 & 67 \\ | ||
qp & 100 & 0.1 & 0.517064 & 0.731825 & 0.722021 & 67 & 67 \\ | ||
qp & 100 & 0.2 & 0.470327 & 0.731825 & 0.722021 & 67 & 67 \\ | ||
qp & 100 & 0.3 & 0.360726 & 0.731825 & 0.722020 & 67 & 67 \\ | ||
bcqp & 1 & 0.1 & 0.840952 & 0.731073 & 0.721200 & 67 & 67 \\ | ||
bcqp & 1 & 0.2 & 0.880100 & 0.731073 & 0.721199 & 67 & 67 \\ | ||
bcqp & 1 & 0.3 & 0.884336 & 0.731073 & 0.721199 & 67 & 67 \\ | ||
qp & 1 & 0.1 & 1.064520 & 0.876534 & 0.870926 & 67 & 67 \\ | ||
qp & 1 & 0.2 & 1.118590 & 0.876534 & 0.870927 & 67 & 67 \\ | ||
qp & 1 & 0.3 & 0.981236 & 0.876534 & 0.870927 & 67 & 67 \\ | ||
bcqp & 10 & 0.1 & 0.849611 & 0.733638 & 0.723925 & 67 & 67 \\ | ||
bcqp & 10 & 0.2 & 0.778322 & 0.733638 & 0.723924 & 67 & 67 \\ | ||
bcqp & 10 & 0.3 & 0.762222 & 0.733638 & 0.723924 & 67 & 67 \\ | ||
qp & 10 & 0.1 & 0.817001 & 0.731825 & 0.722021 & 67 & 67 \\ | ||
qp & 10 & 0.2 & 0.758636 & 0.731825 & 0.722021 & 67 & 67 \\ | ||
qp & 10 & 0.3 & 0.758262 & 0.731825 & 0.722020 & 67 & 67 \\ | ||
bcqp & 100 & 0.1 & 0.698911 & 0.733638 & 0.723925 & 67 & 67 \\ | ||
bcqp & 100 & 0.2 & 0.695293 & 0.733638 & 0.723924 & 67 & 67 \\ | ||
bcqp & 100 & 0.3 & 0.647260 & 0.733638 & 0.723924 & 67 & 67 \\ | ||
qp & 100 & 0.1 & 0.690645 & 0.731825 & 0.722021 & 67 & 67 \\ | ||
qp & 100 & 0.2 & 0.608646 & 0.731825 & 0.722021 & 67 & 67 \\ | ||
qp & 100 & 0.3 & 0.455725 & 0.731825 & 0.722020 & 67 & 67 \\ | ||
\bottomrule | ||
\end{tabular} |
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@@ -1,24 +1,24 @@ | ||
\begin{tabular}{lllrrrrr} | ||
\toprule | ||
optimizer & kernel & C & fit\_time & train\_accuracy & test\_accuracy & nr\_train\_sv & nr\_test\_sv \\ | ||
solver & kernel & C & fit\_time & train\_accuracy & val\_accuracy & nr\_train\_sv & nr\_val\_sv \\ | ||
\midrule | ||
cvxopt & poly & 1 & 0.253555 & 1.0 & 0.994987 & 8 & 8 \\ | ||
libsvm & poly & 1 & 0.003886 & 1.0 & 0.994987 & 7 & 7 \\ | ||
smo & poly & 1 & 0.446164 & 1.0 & 0.997494 & 8 & 8 \\ | ||
cvxopt & rbf & 1 & 0.065434 & 1.0 & 1.000000 & 42 & 42 \\ | ||
libsvm & rbf & 1 & 0.006386 & 1.0 & 1.000000 & 38 & 38 \\ | ||
smo & rbf & 1 & 0.787757 & 1.0 & 1.000000 & 40 & 40 \\ | ||
cvxopt & poly & 10 & 0.100806 & 1.0 & 0.994987 & 8 & 8 \\ | ||
libsvm & poly & 10 & 0.003939 & 1.0 & 0.994987 & 7 & 7 \\ | ||
smo & poly & 10 & 0.274295 & 1.0 & 0.997494 & 8 & 8 \\ | ||
cvxopt & rbf & 10 & 0.065290 & 1.0 & 1.000000 & 42 & 42 \\ | ||
libsvm & rbf & 10 & 0.005806 & 1.0 & 1.000000 & 36 & 36 \\ | ||
smo & rbf & 10 & 0.636188 & 1.0 & 1.000000 & 38 & 38 \\ | ||
cvxopt & poly & 100 & 0.108034 & 1.0 & 0.994987 & 8 & 8 \\ | ||
libsvm & poly & 100 & 0.004066 & 1.0 & 0.994987 & 7 & 7 \\ | ||
smo & poly & 100 & 0.304340 & 1.0 & 0.997494 & 8 & 8 \\ | ||
cvxopt & rbf & 100 & 0.078396 & 1.0 & 1.000000 & 41 & 41 \\ | ||
libsvm & rbf & 100 & 0.005325 & 1.0 & 1.000000 & 36 & 36 \\ | ||
smo & rbf & 100 & 0.382007 & 1.0 & 1.000000 & 38 & 38 \\ | ||
cvxopt & poly & 1 & 0.224446 & 0.878657 & 0.696293 & 25 & 25 \\ | ||
libsvm & poly & 1 & 0.008651 & 1.000000 & 0.997494 & 24 & 24 \\ | ||
smo & poly & 1 & 1.467505 & 0.881154 & 0.691318 & 25 & 25 \\ | ||
cvxopt & rbf & 1 & 0.076681 & 1.000000 & 1.000000 & 42 & 42 \\ | ||
libsvm & rbf & 1 & 0.007161 & 1.000000 & 1.000000 & 40 & 40 \\ | ||
smo & rbf & 1 & 0.396867 & 1.000000 & 1.000000 & 42 & 42 \\ | ||
cvxopt & poly & 10 & 0.091701 & 0.884965 & 0.728482 & 10 & 10 \\ | ||
libsvm & poly & 10 & 0.008077 & 1.000000 & 0.997494 & 9 & 9 \\ | ||
smo & poly & 10 & 1.106135 & 0.886218 & 0.725975 & 10 & 10 \\ | ||
cvxopt & rbf & 10 & 0.085812 & 1.000000 & 1.000000 & 15 & 15 \\ | ||
libsvm & rbf & 10 & 0.007587 & 1.000000 & 1.000000 & 13 & 13 \\ | ||
smo & rbf & 10 & 0.259829 & 1.000000 & 1.000000 & 15 & 15 \\ | ||
cvxopt & poly & 100 & 0.092667 & 0.966259 & 0.920323 & 8 & 8 \\ | ||
libsvm & poly & 100 & 0.008358 & 1.000000 & 0.997494 & 8 & 8 \\ | ||
smo & poly & 100 & 0.919512 & 0.966259 & 0.917817 & 8 & 8 \\ | ||
cvxopt & rbf & 100 & 0.081729 & 1.000000 & 1.000000 & 12 & 12 \\ | ||
libsvm & rbf & 100 & 0.005648 & 1.000000 & 1.000000 & 11 & 11 \\ | ||
smo & rbf & 100 & 0.235654 & 1.000000 & 1.000000 & 12 & 12 \\ | ||
\bottomrule | ||
\end{tabular} |
26 changes: 13 additions & 13 deletions
26
notebooks/ml/tex/experiments/nonlinear_lagrangian_dual_svc.tex
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@@ -1,18 +1,18 @@ | ||
\begin{tabular}{lllrrrrr} | ||
\toprule | ||
ld & kernel & C & fit\_time & train\_accuracy & test\_accuracy & nr\_train\_sv & nr\_test\_sv \\ | ||
ld & kernel & C & fit\_time & train\_accuracy & val\_accuracy & nr\_train\_sv & nr\_val\_sv \\ | ||
\midrule | ||
bcqp & poly & 1 & 3.186200 & 0.853759 & 0.728145 & 212 & 212 \\ | ||
bcqp & rbf & 1 & 0.044137 & 1.000000 & 1.000000 & 205 & 205 \\ | ||
qp & poly & 1 & 0.117401 & 0.823787 & 0.738095 & 163 & 163 \\ | ||
qp & rbf & 1 & 1.696029 & 1.000000 & 0.997494 & 143 & 143 \\ | ||
bcqp & poly & 10 & 2.776435 & 0.853759 & 0.728145 & 212 & 212 \\ | ||
bcqp & rbf & 10 & 0.035251 & 1.000000 & 1.000000 & 205 & 205 \\ | ||
qp & poly & 10 & 0.134212 & 0.823787 & 0.738095 & 163 & 163 \\ | ||
qp & rbf & 10 & 1.086226 & 0.998752 & 0.997494 & 142 & 142 \\ | ||
bcqp & poly & 100 & 2.888524 & 0.853759 & 0.728145 & 212 & 212 \\ | ||
bcqp & rbf & 100 & 0.035742 & 1.000000 & 1.000000 & 205 & 205 \\ | ||
qp & poly & 100 & 0.048170 & 0.823787 & 0.738095 & 163 & 163 \\ | ||
qp & rbf & 100 & 0.941620 & 1.000000 & 0.997494 & 142 & 142 \\ | ||
bcqp & poly & 1 & 0.078685 & 0.750007 & 0.501253 & 217 & 217 \\ | ||
bcqp & rbf & 1 & 0.028115 & 1.000000 & 0.997512 & 241 & 241 \\ | ||
qp & poly & 1 & 0.737430 & 0.872504 & 0.750627 & 138 & 138 \\ | ||
qp & rbf & 1 & 1.608392 & 0.800071 & 0.635656 & 188 & 188 \\ | ||
bcqp & poly & 10 & 0.073986 & 0.750007 & 0.501253 & 217 & 217 \\ | ||
bcqp & rbf & 10 & 0.021263 & 1.000000 & 0.997512 & 241 & 241 \\ | ||
qp & poly & 10 & 0.741292 & 0.872504 & 0.750627 & 138 & 138 \\ | ||
qp & rbf & 10 & 1.405860 & 0.857500 & 0.718400 & 199 & 199 \\ | ||
bcqp & poly & 100 & 0.063981 & 0.750007 & 0.501253 & 217 & 217 \\ | ||
bcqp & rbf & 100 & 0.025343 & 1.000000 & 0.997512 & 241 & 241 \\ | ||
qp & poly & 100 & 0.571038 & 0.872504 & 0.750627 & 138 & 138 \\ | ||
qp & rbf & 100 & 0.761562 & 0.782584 & 0.608218 & 154 & 154 \\ | ||
\bottomrule | ||
\end{tabular} |
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