GMS location: 817
Random forest results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.978 |
0.235 |
0.719 |
0.586 |
4.400 |
NaN |
NaN |
forest |
winter 2016 |
0.995 |
0.118 |
0.680 |
0.567 |
4.509 |
0.422 |
2.554 |
baseline |
winter 2017 |
0.974 |
0.000e+00 |
0.280 |
0.366 |
1.877 |
NaN |
NaN |
forest |
winter 2017 |
0.974 |
0.000e+00 |
0.252 |
0.366 |
1.808 |
0.426 |
1.501 |
baseline |
winter 2018 |
0.987 |
0.000e+00 |
0.404 |
0.460 |
2.215 |
NaN |
NaN |
forest |
winter 2018 |
1.000 |
0.042 |
0.338 |
0.436 |
1.926 |
0.407 |
1.453 |
baseline |
winter 2019 |
0.965 |
0.000e+00 |
0.407 |
0.454 |
2.217 |
NaN |
NaN |
forest |
winter 2019 |
0.986 |
0.000e+00 |
0.308 |
0.401 |
1.851 |
0.399 |
1.366 |
baseline |
all |
0.977 |
0.046 |
0.471 |
0.476 |
4.400 |
NaN |
NaN |
forest |
all |
0.990 |
0.035 |
0.414 |
0.452 |
4.509 |
0.414 |
1.768 |
Random forest plots
Extended logistic regression results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.978 |
0.235 |
0.719 |
0.586 |
4.400 |
NaN |
NaN |
elr |
winter 2016 |
0.989 |
0.176 |
0.680 |
0.560 |
4.157 |
0.472 |
2.993 |
baseline |
winter 2017 |
0.974 |
0.000e+00 |
0.280 |
0.366 |
1.877 |
NaN |
NaN |
elr |
winter 2017 |
0.966 |
0.000e+00 |
0.248 |
0.373 |
1.550 |
0.482 |
1.820 |
baseline |
winter 2018 |
0.987 |
0.000e+00 |
0.404 |
0.460 |
2.215 |
NaN |
NaN |
elr |
winter 2018 |
0.994 |
0.000e+00 |
0.330 |
0.441 |
1.921 |
0.448 |
1.732 |
baseline |
winter 2019 |
0.965 |
0.000e+00 |
0.407 |
0.454 |
2.217 |
NaN |
NaN |
elr |
winter 2019 |
0.993 |
0.000e+00 |
0.312 |
0.413 |
1.905 |
0.421 |
1.457 |
baseline |
all |
0.977 |
0.046 |
0.471 |
0.476 |
4.400 |
NaN |
NaN |
elr |
all |
0.987 |
0.035 |
0.412 |
0.456 |
4.157 |
0.456 |
2.059 |
Extended logistic regression plots