GMS location: 414
Random forest results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.967 |
0.043 |
0.333 |
0.435 |
1.627 |
NaN |
NaN |
forest |
winter 2016 |
0.973 |
0.043 |
0.295 |
0.400 |
1.709 |
0.503 |
4.537 |
baseline |
winter 2017 |
0.963 |
0.024 |
0.385 |
0.442 |
2.574 |
NaN |
NaN |
forest |
winter 2017 |
0.973 |
0.073 |
0.287 |
0.377 |
2.093 |
0.475 |
3.381 |
baseline |
winter 2018 |
1.000 |
0.094 |
0.363 |
0.450 |
2.479 |
NaN |
NaN |
forest |
winter 2018 |
1.000 |
0.094 |
0.304 |
0.425 |
2.358 |
0.482 |
4.097 |
baseline |
winter 2019 |
0.986 |
0.000e+00 |
0.310 |
0.381 |
2.507 |
NaN |
NaN |
forest |
winter 2019 |
0.993 |
0.000e+00 |
0.236 |
0.349 |
1.766 |
0.474 |
2.850 |
baseline |
all |
0.979 |
0.045 |
0.346 |
0.427 |
2.574 |
NaN |
NaN |
forest |
all |
0.984 |
0.063 |
0.281 |
0.389 |
2.358 |
0.485 |
3.776 |
Random forest plots
Extended logistic regression results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.967 |
0.043 |
0.333 |
0.435 |
1.627 |
NaN |
NaN |
elr |
winter 2016 |
0.973 |
0.000e+00 |
0.314 |
0.435 |
1.658 |
0.570 |
4.952 |
baseline |
winter 2017 |
0.963 |
0.024 |
0.385 |
0.442 |
2.574 |
NaN |
NaN |
elr |
winter 2017 |
0.954 |
0.024 |
0.328 |
0.406 |
2.186 |
0.526 |
4.472 |
baseline |
winter 2018 |
1.000 |
0.094 |
0.363 |
0.450 |
2.479 |
NaN |
NaN |
elr |
winter 2018 |
1.000 |
0.094 |
0.307 |
0.438 |
2.453 |
0.537 |
4.336 |
baseline |
winter 2019 |
0.986 |
0.000e+00 |
0.310 |
0.381 |
2.507 |
NaN |
NaN |
elr |
winter 2019 |
0.993 |
0.000e+00 |
0.275 |
0.394 |
1.854 |
0.516 |
3.978 |
baseline |
all |
0.979 |
0.045 |
0.346 |
0.427 |
2.574 |
NaN |
NaN |
elr |
all |
0.980 |
0.036 |
0.306 |
0.419 |
2.453 |
0.540 |
4.471 |
Extended logistic regression plots