GMS location: 567
Random forest results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
1.000 |
0.000e+00 |
0.327 |
0.433 |
2.002 |
NaN |
NaN |
forest |
winter 2016 |
1.000 |
0.000e+00 |
0.301 |
0.418 |
1.808 |
0.524 |
3.955 |
baseline |
winter 2017 |
0.991 |
0.031 |
0.346 |
0.439 |
1.891 |
NaN |
NaN |
forest |
winter 2017 |
0.982 |
0.031 |
0.279 |
0.386 |
1.492 |
0.517 |
3.926 |
baseline |
winter 2018 |
1.000 |
0.185 |
0.291 |
0.404 |
1.915 |
NaN |
NaN |
forest |
winter 2018 |
0.994 |
0.222 |
0.248 |
0.373 |
1.571 |
0.528 |
2.851 |
baseline |
winter 2019 |
0.994 |
0.083 |
0.345 |
0.427 |
2.101 |
NaN |
NaN |
forest |
winter 2019 |
0.987 |
0.083 |
0.303 |
0.404 |
1.843 |
0.521 |
3.574 |
baseline |
all |
0.997 |
0.081 |
0.326 |
0.425 |
2.101 |
NaN |
NaN |
forest |
all |
0.992 |
0.093 |
0.283 |
0.396 |
1.843 |
0.523 |
3.570 |
Random forest plots
Extended logistic regression results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
1.000 |
0.000e+00 |
0.327 |
0.433 |
2.002 |
NaN |
NaN |
elr |
winter 2016 |
1.000 |
0.000e+00 |
0.319 |
0.438 |
1.709 |
0.602 |
5.543 |
baseline |
winter 2017 |
0.991 |
0.031 |
0.346 |
0.439 |
1.891 |
NaN |
NaN |
elr |
winter 2017 |
0.982 |
0.031 |
0.326 |
0.437 |
1.746 |
0.595 |
5.039 |
baseline |
winter 2018 |
1.000 |
0.185 |
0.291 |
0.404 |
1.915 |
NaN |
NaN |
elr |
winter 2018 |
0.994 |
0.148 |
0.256 |
0.379 |
1.666 |
0.576 |
3.952 |
baseline |
winter 2019 |
0.994 |
0.083 |
0.345 |
0.427 |
2.101 |
NaN |
NaN |
elr |
winter 2019 |
0.994 |
0.083 |
0.334 |
0.445 |
1.829 |
0.527 |
4.101 |
baseline |
all |
0.997 |
0.081 |
0.326 |
0.425 |
2.101 |
NaN |
NaN |
elr |
all |
0.993 |
0.070 |
0.307 |
0.424 |
1.829 |
0.576 |
4.682 |
Extended logistic regression plots