GMS location: 811
Random forest results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.978 |
0.000e+00 |
0.392 |
0.444 |
2.834 |
NaN |
NaN |
forest |
winter 2016 |
0.962 |
0.048 |
0.389 |
0.453 |
2.498 |
0.535 |
3.178 |
baseline |
winter 2017 |
0.991 |
0.108 |
0.305 |
0.398 |
1.901 |
NaN |
NaN |
forest |
winter 2017 |
0.991 |
0.135 |
0.284 |
0.394 |
1.987 |
0.510 |
2.858 |
baseline |
winter 2018 |
0.987 |
0.161 |
0.441 |
0.481 |
2.230 |
NaN |
NaN |
forest |
winter 2018 |
0.980 |
0.129 |
0.352 |
0.432 |
2.376 |
0.526 |
2.985 |
baseline |
winter 2019 |
0.985 |
0.231 |
0.401 |
0.475 |
2.159 |
NaN |
NaN |
forest |
winter 2019 |
0.985 |
0.231 |
0.321 |
0.418 |
2.311 |
0.520 |
2.499 |
baseline |
all |
0.985 |
0.130 |
0.388 |
0.451 |
2.834 |
NaN |
NaN |
forest |
all |
0.978 |
0.139 |
0.341 |
0.427 |
2.498 |
0.524 |
2.905 |
Random forest plots
Extended logistic regression results
names |
period |
power |
significance |
meanSquareError |
absError |
maxError |
CRPS |
IGN |
baseline |
winter 2016 |
0.978 |
0.000e+00 |
0.392 |
0.444 |
2.834 |
NaN |
NaN |
elr |
winter 2016 |
0.962 |
0.000e+00 |
0.418 |
0.485 |
2.646 |
0.616 |
4.015 |
baseline |
winter 2017 |
0.991 |
0.108 |
0.305 |
0.398 |
1.901 |
NaN |
NaN |
elr |
winter 2017 |
1.000 |
0.054 |
0.292 |
0.404 |
2.135 |
0.559 |
2.991 |
baseline |
winter 2018 |
0.987 |
0.161 |
0.441 |
0.481 |
2.230 |
NaN |
NaN |
elr |
winter 2018 |
0.980 |
0.097 |
0.394 |
0.458 |
2.308 |
0.559 |
3.426 |
baseline |
winter 2019 |
0.985 |
0.231 |
0.401 |
0.475 |
2.159 |
NaN |
NaN |
elr |
winter 2019 |
0.985 |
0.154 |
0.339 |
0.439 |
2.570 |
0.560 |
3.038 |
baseline |
all |
0.985 |
0.130 |
0.388 |
0.451 |
2.834 |
NaN |
NaN |
elr |
all |
0.979 |
0.078 |
0.366 |
0.450 |
2.646 |
0.576 |
3.418 |
Extended logistic regression plots