GMS location: 1215
Random forest results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.969 |
0.100 |
0.367 |
0.444 |
2.628 |
NaN |
NaN |
forest |
winter 2016 |
0.963 |
0.000e+00 |
0.290 |
0.398 |
2.434 |
0.542 |
2.741 |
baseline |
winter 2017 |
0.992 |
0.056 |
0.609 |
0.571 |
2.356 |
NaN |
NaN |
forest |
winter 2017 |
1.000 |
0.056 |
0.475 |
0.508 |
2.450 |
0.516 |
3.136 |
baseline |
winter 2018 |
0.993 |
0.105 |
0.446 |
0.490 |
2.468 |
NaN |
NaN |
forest |
winter 2018 |
0.979 |
0.079 |
0.404 |
0.470 |
2.354 |
0.540 |
2.493 |
baseline |
winter 2019 |
0.987 |
0.000e+00 |
0.331 |
0.410 |
2.311 |
NaN |
NaN |
forest |
winter 2019 |
0.981 |
0.000e+00 |
0.286 |
0.399 |
2.179 |
0.537 |
2.497 |
baseline |
all |
0.984 |
0.078 |
0.432 |
0.476 |
2.628 |
NaN |
NaN |
forest |
all |
0.979 |
0.043 |
0.360 |
0.441 |
2.450 |
0.534 |
2.704 |
Random forest plots
Extended logistic regression results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.969 |
0.100 |
0.367 |
0.444 |
2.628 |
NaN |
NaN |
elr |
winter 2016 |
0.963 |
0.033 |
0.332 |
0.448 |
2.413 |
0.642 |
3.375 |
baseline |
winter 2017 |
0.992 |
0.056 |
0.609 |
0.571 |
2.356 |
NaN |
NaN |
elr |
winter 2017 |
1.000 |
0.056 |
0.478 |
0.521 |
2.346 |
0.577 |
3.735 |
baseline |
winter 2018 |
0.993 |
0.105 |
0.446 |
0.490 |
2.468 |
NaN |
NaN |
elr |
winter 2018 |
0.979 |
0.105 |
0.422 |
0.501 |
2.359 |
0.625 |
3.791 |
baseline |
winter 2019 |
0.987 |
0.000e+00 |
0.331 |
0.410 |
2.311 |
NaN |
NaN |
elr |
winter 2019 |
0.981 |
0.000e+00 |
0.340 |
0.458 |
2.097 |
0.597 |
3.145 |
baseline |
all |
0.984 |
0.078 |
0.432 |
0.476 |
2.628 |
NaN |
NaN |
elr |
all |
0.979 |
0.060 |
0.390 |
0.480 |
2.413 |
0.612 |
3.508 |
Extended logistic regression plots