GMS location: 1157
Random forest results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.994 |
0.000e+00 |
0.317 |
0.411 |
2.418 |
NaN |
NaN |
forest |
winter 2016 |
0.989 |
0.000e+00 |
0.263 |
0.378 |
1.977 |
0.524 |
2.825 |
baseline |
winter 2017 |
0.973 |
0.027 |
0.543 |
0.529 |
2.312 |
NaN |
NaN |
forest |
winter 2017 |
0.973 |
0.027 |
0.417 |
0.463 |
2.092 |
0.509 |
3.929 |
baseline |
winter 2018 |
0.986 |
0.133 |
0.312 |
0.410 |
2.300 |
NaN |
NaN |
forest |
winter 2018 |
0.993 |
0.133 |
0.263 |
0.382 |
2.119 |
0.516 |
2.653 |
baseline |
winter 2019 |
0.993 |
0.091 |
0.440 |
0.422 |
4.495 |
NaN |
NaN |
forest |
winter 2019 |
0.993 |
0.091 |
0.360 |
0.393 |
4.423 |
0.541 |
3.785 |
baseline |
all |
0.988 |
0.054 |
0.392 |
0.439 |
4.495 |
NaN |
NaN |
forest |
all |
0.988 |
0.054 |
0.318 |
0.401 |
4.423 |
0.522 |
3.235 |
Random forest plots
Extended logistic regression results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.994 |
0.000e+00 |
0.317 |
0.411 |
2.418 |
NaN |
NaN |
elr |
winter 2016 |
0.989 |
0.000e+00 |
0.308 |
0.427 |
2.087 |
0.626 |
4.191 |
baseline |
winter 2017 |
0.973 |
0.027 |
0.543 |
0.529 |
2.312 |
NaN |
NaN |
elr |
winter 2017 |
0.982 |
0.027 |
0.448 |
0.495 |
1.826 |
0.575 |
4.380 |
baseline |
winter 2018 |
0.986 |
0.133 |
0.312 |
0.410 |
2.300 |
NaN |
NaN |
elr |
winter 2018 |
0.993 |
0.133 |
0.306 |
0.445 |
1.947 |
0.578 |
3.770 |
baseline |
winter 2019 |
0.993 |
0.091 |
0.440 |
0.422 |
4.495 |
NaN |
NaN |
elr |
winter 2019 |
0.993 |
0.091 |
0.403 |
0.427 |
4.385 |
0.560 |
3.846 |
baseline |
all |
0.988 |
0.054 |
0.392 |
0.439 |
4.495 |
NaN |
NaN |
elr |
all |
0.990 |
0.054 |
0.359 |
0.446 |
4.385 |
0.588 |
4.047 |
Extended logistic regression plots