GMS location: 962
Random forest results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
1.000 |
0.000e+00 |
0.457 |
0.478 |
3.176 |
NaN |
NaN |
forest |
winter 2016 |
0.973 |
0.000e+00 |
0.436 |
0.481 |
3.246 |
0.530 |
4.728 |
baseline |
winter 2017 |
0.983 |
0.083 |
0.459 |
0.466 |
2.730 |
NaN |
NaN |
forest |
winter 2017 |
0.957 |
0.000e+00 |
0.397 |
0.437 |
2.571 |
0.540 |
2.305 |
baseline |
winter 2018 |
0.980 |
0.156 |
0.328 |
0.384 |
2.241 |
NaN |
NaN |
forest |
winter 2018 |
0.970 |
0.094 |
0.321 |
0.415 |
2.028 |
0.541 |
2.226 |
baseline |
all |
0.990 |
0.092 |
0.422 |
0.449 |
3.176 |
NaN |
NaN |
forest |
all |
0.968 |
0.035 |
0.393 |
0.450 |
3.246 |
0.536 |
3.295 |
Random forest plots
Extended logistic regression results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
1.000 |
0.000e+00 |
0.457 |
0.478 |
3.176 |
NaN |
NaN |
elr |
winter 2016 |
0.968 |
0.053 |
0.396 |
0.465 |
2.952 |
0.677 |
4.927 |
baseline |
winter 2017 |
0.983 |
0.083 |
0.459 |
0.466 |
2.730 |
NaN |
NaN |
elr |
winter 2017 |
0.966 |
0.000e+00 |
0.409 |
0.457 |
2.305 |
0.640 |
3.871 |
baseline |
winter 2018 |
0.980 |
0.156 |
0.328 |
0.384 |
2.241 |
NaN |
NaN |
elr |
winter 2018 |
0.980 |
0.125 |
0.391 |
0.472 |
2.046 |
0.589 |
3.255 |
baseline |
all |
0.990 |
0.092 |
0.422 |
0.449 |
3.176 |
NaN |
NaN |
elr |
all |
0.970 |
0.058 |
0.399 |
0.464 |
2.952 |
0.642 |
4.144 |
Extended logistic regression plots