model |
notes |
training time |
prediction time |
cross validation RMSE |
cross validation classification error |
test RMSE |
test classification error |
LR - linear regression |
15 search epochs, λ=0.000524479 |
1[s] |
0[s] |
0.346912 |
44.7062% |
0.348054 |
45.575% |
PR - polynomial regression |
15 search epochs, polyOrder=4, λ=0.00349871, crossInteractions=yes |
310[s] |
4[s] |
0.212869 |
7.51875% |
0.214539 |
7.35% |
GBDT - gradient boosted decision tree |
500 epochs, featureSubspaceSize=5, maxTreeLeafes=100, η=0.1, optSplitPoint=no |
8332[s] |
14[s] |
0.134175 |
3.41875% |
0.135784 |
3.275% |
KNN - k-nearest neighbors |
15 search epochs, distance=euclidean, k=3 |
27[s] |
3[s] |
0.112202 |
5.21875% |
0.111163 |
5% |
NN - neural network |
1000 epochs, stochastic gradient descent, Net: 17-70-50-26, η=0.001, λ=0 |
866[s] |
0[s] |
0.124753 |
4.68125% |
0.122801 |
4.325% |
KRR - kernel ridge regression |
30 search epochs, gauss kernel, sigma=2.46455, λ=1.1675e-06 |
2432[s] |
6[s] |
0.129338 |
2.4% |
0.127372 |
2.35% |
model |
notes |
training time |
prediction time |
cross validation RMSE |
cross validation classification error |
test RMSE |
test classification error |
LR - linear regression |
15 search epochs, λ=0.0149426 |
0[s] |
0[s] |
0.497712 |
23.8106% |
0.509548 |
25.85% |
PR - polynomial regression |
15 search epochs, polyOrder=1, λ=0.0158027, crossInteractions=yes |
10[s] |
0[s] |
0.405117 |
13.5964% |
0.417862 |
14.95% |
GBDT - gradient boosted decision tree |
107 epochs, featureSubspaceSize=5, maxTreeLeafes=50, η=0.1, optSplitPoint=yes |
37[s] |
0[s] |
0.315662 |
9.37993% |
0.322224 |
9.5% |
KNN - k-nearest neighbors |
15 search epochs, distance=euclidean, k=4 |
3[s] |
0[s] |
0.300494 |
8.95152% |
0.301169 |
9.1% |
NN - neural network |
329 epochs, stochastic gradient descent, Net: 37-70-50-6 , η=0.001, λ=0 |
64[s] |
0[s] |
0.30259 |
8.97407% |
0.304153 |
9.05% |
KRR - kernel ridge regression |
30 search epochs, gauss kernel, sigma=3.18697, λ=1.66922e-05 |
65[s] |
1[s] |
0.297553 |
7.64374% |
0.305151 |
8.45% |
model |
notes |
training time |
prediction time |
cross validation RMSE |
cross validation classification error |
test RMSE |
test classification error |
LR - linear regression |
15 search epochs, λ=0.0592731 |
3[s] |
0[s] |
0.681173 |
16.0806% |
0.678574 |
15.7423% |
PR - polynomial regression |
15 search epochs, polyOrder=2, λ=0.00110125, crossInteractions=no |
12[s] |
0[s] |
0.662291 |
14.9412% |
0.66019 |
14.7288% |
GBDT - gradient boosted decision tree |
162 epochs, featureSubspaceSize=10, maxTreeLeafes=50, η=0.1, optSplitPoint=yes |
140[s] |
1[s] |
0.60082 |
12.7607% |
0.601293 |
12.7019% |
KNN - k-nearest neighbors |
15 search epochs, distance=euclidean, k=13 |
155[s] |
88[s] |
0.814904 |
21.3753% |
0.811027 |
20.9139% |
NN - neural network |
16 epochs, stochastic gradient descent, Net: 109-30-20-2 , η=0.001, λ=0 |
45[s] |
1[s] |
0.635936 |
14.5757% |
0.637256 |
14.7595% |
KRR - kernel ridge regression |
30 search epochs, gauss kernel, sigma=19.1556, λ=1.1675e-05, (maxThreadsInCross=2) |
36148[s] |
83[s] |
0.644849 |
14.932% |
0.64379 |
14.6797% |