GMS location: 506
Random forest results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.989 |
0.050 |
0.366 |
0.476 |
1.828 |
NaN |
NaN |
forest |
winter 2016 |
0.994 |
0.050 |
0.309 |
0.418 |
2.185 |
0.455 |
3.078 |
baseline |
winter 2017 |
0.952 |
0.036 |
0.470 |
0.526 |
2.276 |
NaN |
NaN |
forest |
winter 2017 |
0.968 |
0.036 |
0.383 |
0.468 |
2.126 |
0.472 |
3.422 |
baseline |
winter 2019 |
0.993 |
0.083 |
0.260 |
0.380 |
1.828 |
NaN |
NaN |
forest |
winter 2019 |
0.993 |
0.083 |
0.271 |
0.401 |
1.372 |
0.475 |
2.429 |
baseline |
all |
0.980 |
0.050 |
0.363 |
0.461 |
2.276 |
NaN |
NaN |
forest |
all |
0.987 |
0.050 |
0.319 |
0.428 |
2.185 |
0.467 |
2.976 |
Random forest plots
Extended logistic regression results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.989 |
0.050 |
0.366 |
0.476 |
1.828 |
NaN |
NaN |
elr |
winter 2016 |
0.983 |
0.050 |
0.363 |
0.476 |
2.166 |
0.551 |
4.949 |
baseline |
winter 2017 |
0.952 |
0.036 |
0.470 |
0.526 |
2.276 |
NaN |
NaN |
elr |
winter 2017 |
0.968 |
0.036 |
0.406 |
0.480 |
2.381 |
0.504 |
4.926 |
baseline |
winter 2019 |
0.993 |
0.083 |
0.260 |
0.380 |
1.828 |
NaN |
NaN |
elr |
winter 2019 |
0.993 |
0.083 |
0.273 |
0.398 |
1.603 |
0.504 |
3.372 |
baseline |
all |
0.980 |
0.050 |
0.363 |
0.461 |
2.276 |
NaN |
NaN |
elr |
all |
0.982 |
0.050 |
0.347 |
0.453 |
2.381 |
0.522 |
4.442 |
Extended logistic regression plots