GMS location: 814
Random forest results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.984 |
0.000e+00 |
0.312 |
0.426 |
1.863 |
NaN |
NaN |
forest |
winter 2016 |
0.995 |
0.000e+00 |
0.259 |
0.380 |
1.841 |
0.472 |
4.195 |
baseline |
winter 2017 |
0.991 |
0.056 |
0.291 |
0.406 |
1.827 |
NaN |
NaN |
forest |
winter 2017 |
1.000 |
0.056 |
0.212 |
0.333 |
1.439 |
0.465 |
4.261 |
baseline |
winter 2018 |
0.979 |
0.053 |
0.357 |
0.424 |
2.447 |
NaN |
NaN |
forest |
winter 2018 |
0.972 |
0.000e+00 |
0.293 |
0.386 |
2.356 |
0.477 |
4.258 |
baseline |
winter 2019 |
1.000 |
0.077 |
0.297 |
0.389 |
1.874 |
NaN |
NaN |
forest |
winter 2019 |
1.000 |
0.077 |
0.275 |
0.378 |
2.238 |
0.437 |
2.857 |
baseline |
all |
0.988 |
0.048 |
0.315 |
0.413 |
2.447 |
NaN |
NaN |
forest |
all |
0.991 |
0.036 |
0.260 |
0.370 |
2.356 |
0.464 |
3.944 |
Random forest plots
Extended logistic regression results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.984 |
0.000e+00 |
0.312 |
0.426 |
1.863 |
NaN |
NaN |
elr |
winter 2016 |
0.979 |
0.067 |
0.285 |
0.410 |
1.716 |
0.570 |
6.659 |
baseline |
winter 2017 |
0.991 |
0.056 |
0.291 |
0.406 |
1.827 |
NaN |
NaN |
elr |
winter 2017 |
0.983 |
0.028 |
0.214 |
0.371 |
1.452 |
0.562 |
4.881 |
baseline |
winter 2018 |
0.979 |
0.053 |
0.357 |
0.424 |
2.447 |
NaN |
NaN |
elr |
winter 2018 |
0.972 |
0.000e+00 |
0.284 |
0.399 |
2.070 |
0.519 |
5.562 |
baseline |
winter 2019 |
1.000 |
0.077 |
0.297 |
0.389 |
1.874 |
NaN |
NaN |
elr |
winter 2019 |
1.000 |
0.000e+00 |
0.260 |
0.367 |
2.011 |
0.508 |
4.548 |
baseline |
all |
0.988 |
0.048 |
0.315 |
0.413 |
2.447 |
NaN |
NaN |
elr |
all |
0.983 |
0.024 |
0.263 |
0.389 |
2.070 |
0.542 |
5.530 |
Extended logistic regression plots