GMS location: 925
Random forest results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.978 |
0.000e+00 |
0.338 |
0.433 |
1.756 |
NaN |
NaN |
forest |
winter 2016 |
0.989 |
0.000e+00 |
0.260 |
0.378 |
1.593 |
0.471 |
6.539 |
baseline |
winter 2018 |
0.984 |
0.056 |
0.202 |
0.340 |
1.900 |
NaN |
NaN |
forest |
winter 2018 |
0.984 |
0.111 |
0.172 |
0.307 |
1.873 |
0.458 |
3.064 |
baseline |
winter 2019 |
1.000 |
0.000e+00 |
0.283 |
0.406 |
1.641 |
NaN |
NaN |
forest |
winter 2019 |
1.000 |
0.000e+00 |
0.205 |
0.345 |
1.232 |
0.471 |
4.403 |
baseline |
all |
0.986 |
0.030 |
0.280 |
0.396 |
1.900 |
NaN |
NaN |
forest |
all |
0.990 |
0.061 |
0.218 |
0.347 |
1.873 |
0.467 |
4.883 |
Random forest plots
Extended logistic regression results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.978 |
0.000e+00 |
0.338 |
0.433 |
1.756 |
NaN |
NaN |
elr |
winter 2016 |
0.978 |
0.000e+00 |
0.276 |
0.401 |
1.803 |
0.562 |
1.310e+01 |
baseline |
winter 2018 |
0.984 |
0.056 |
0.202 |
0.340 |
1.900 |
NaN |
NaN |
elr |
winter 2018 |
0.976 |
0.056 |
0.227 |
0.376 |
1.808 |
0.565 |
7.895 |
baseline |
winter 2019 |
1.000 |
0.000e+00 |
0.283 |
0.406 |
1.641 |
NaN |
NaN |
elr |
winter 2019 |
1.000 |
0.000e+00 |
0.216 |
0.358 |
1.338 |
0.498 |
5.679 |
baseline |
all |
0.986 |
0.030 |
0.280 |
0.396 |
1.900 |
NaN |
NaN |
elr |
all |
0.983 |
0.030 |
0.245 |
0.382 |
1.808 |
0.547 |
9.544 |
Extended logistic regression plots