GMS location: 1015
Random forest results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2017 |
0.983 |
0.114 |
0.639 |
0.544 |
3.500 |
NaN |
NaN |
forest |
winter 2017 |
0.975 |
0.086 |
0.574 |
0.532 |
3.374 |
0.566 |
4.049 |
baseline |
winter 2018 |
0.973 |
0.191 |
0.410 |
0.502 |
2.102 |
NaN |
NaN |
forest |
winter 2018 |
0.973 |
0.143 |
0.342 |
0.450 |
1.973 |
0.537 |
2.150 |
baseline |
winter 2019 |
1.000 |
0.118 |
0.348 |
0.440 |
2.097 |
NaN |
NaN |
forest |
winter 2019 |
0.993 |
0.235 |
0.316 |
0.406 |
1.808 |
0.534 |
1.986 |
baseline |
all |
0.985 |
0.137 |
0.464 |
0.496 |
3.500 |
NaN |
NaN |
forest |
all |
0.980 |
0.137 |
0.408 |
0.462 |
3.374 |
0.545 |
2.708 |
Random forest plots
Extended logistic regression results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2017 |
0.983 |
0.114 |
0.639 |
0.544 |
3.500 |
NaN |
NaN |
elr |
winter 2017 |
0.966 |
0.143 |
0.652 |
0.602 |
2.915 |
0.647 |
5.676 |
baseline |
winter 2018 |
0.973 |
0.191 |
0.410 |
0.502 |
2.102 |
NaN |
NaN |
elr |
winter 2018 |
0.980 |
0.143 |
0.370 |
0.476 |
1.883 |
0.608 |
2.776 |
baseline |
winter 2019 |
1.000 |
0.118 |
0.348 |
0.440 |
2.097 |
NaN |
NaN |
elr |
winter 2019 |
1.000 |
0.059 |
0.362 |
0.466 |
2.077 |
0.575 |
2.581 |
baseline |
all |
0.985 |
0.137 |
0.464 |
0.496 |
3.500 |
NaN |
NaN |
elr |
all |
0.983 |
0.123 |
0.458 |
0.513 |
2.915 |
0.610 |
3.645 |
Extended logistic regression plots