GMS location: 451

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.983 0.040 0.555 0.499 4.687 NaN NaN
forest winter 2016 0.983 0.040 0.491 0.465 4.581 0.503 4.895
baseline winter 2017 0.963 0.025 0.399 0.456 2.417 NaN NaN
forest winter 2017 0.963 0.000e+00 0.335 0.410 1.890 0.478 3.315
baseline winter 2018 0.993 0.184 0.316 0.407 2.119 NaN NaN
forest winter 2018 0.993 0.132 0.295 0.401 1.806 0.484 2.506
baseline winter 2019 1.000 0.059 0.344 0.444 1.994 NaN NaN
forest winter 2019 1.000 0.059 0.284 0.402 1.616 0.488 2.830
baseline all 0.985 0.083 0.413 0.454 4.687 NaN NaN
forest all 0.985 0.058 0.361 0.423 4.581 0.489 3.481

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.983 0.040 0.555 0.499 4.687 NaN NaN
elr winter 2016 0.977 0.080 0.507 0.493 4.533 0.571 4.341
baseline winter 2017 0.963 0.025 0.399 0.456 2.417 NaN NaN
elr winter 2017 0.972 0.000e+00 0.381 0.460 2.274 0.541 3.102
baseline winter 2018 0.993 0.184 0.316 0.407 2.119 NaN NaN
elr winter 2018 1.000 0.132 0.314 0.420 2.286 0.542 2.992
baseline winter 2019 1.000 0.059 0.344 0.444 1.994 NaN NaN
elr winter 2019 1.000 0.118 0.299 0.420 1.818 0.509 2.488
baseline all 0.985 0.083 0.413 0.454 4.687 NaN NaN
elr all 0.987 0.075 0.385 0.451 4.533 0.544 3.321

Extended logistic regression plots

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