GMS location: 602
Random forest results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.988 |
0.095 |
0.326 |
0.430 |
2.102 |
NaN |
NaN |
forest |
winter 2016 |
0.983 |
0.095 |
0.281 |
0.391 |
1.859 |
0.542 |
5.024 |
baseline |
winter 2017 |
0.958 |
0.059 |
0.410 |
0.469 |
2.636 |
NaN |
NaN |
forest |
winter 2017 |
0.966 |
0.059 |
0.364 |
0.443 |
2.181 |
0.530 |
4.084 |
baseline |
winter 2019 |
0.992 |
0.000e+00 |
0.323 |
0.421 |
1.704 |
NaN |
NaN |
forest |
winter 2019 |
0.992 |
0.000e+00 |
0.276 |
0.402 |
1.392 |
0.523 |
3.912 |
baseline |
all |
0.981 |
0.061 |
0.352 |
0.440 |
2.636 |
NaN |
NaN |
forest |
all |
0.981 |
0.061 |
0.306 |
0.411 |
2.181 |
0.533 |
4.412 |
Random forest plots
Extended logistic regression results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.988 |
0.095 |
0.326 |
0.430 |
2.102 |
NaN |
NaN |
elr |
winter 2016 |
0.983 |
0.095 |
0.332 |
0.458 |
1.704 |
0.663 |
6.325 |
baseline |
winter 2017 |
0.958 |
0.059 |
0.410 |
0.469 |
2.636 |
NaN |
NaN |
elr |
winter 2017 |
0.950 |
0.029 |
0.407 |
0.465 |
2.531 |
0.584 |
5.309 |
baseline |
winter 2019 |
0.992 |
0.000e+00 |
0.323 |
0.421 |
1.704 |
NaN |
NaN |
elr |
winter 2019 |
1.000 |
0.000e+00 |
0.364 |
0.476 |
1.764 |
0.522 |
3.580 |
baseline |
all |
0.981 |
0.061 |
0.352 |
0.440 |
2.636 |
NaN |
NaN |
elr |
all |
0.978 |
0.045 |
0.365 |
0.465 |
2.531 |
0.599 |
5.233 |
Extended logistic regression plots