GMS location: 1225

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.982 0.097 0.421 0.482 2.125 NaN NaN
forest winter 2016 0.982 0.097 0.316 0.416 1.805 0.501 2.761
baseline winter 2017 0.983 0.028 0.487 0.536 2.285 NaN NaN
forest winter 2017 0.983 0.028 0.366 0.462 1.910 0.501 2.533
baseline winter 2018 0.986 0.068 0.459 0.484 2.564 NaN NaN
forest winter 2018 0.993 0.068 0.363 0.427 2.184 0.509 2.635
baseline winter 2019 0.993 0.059 0.361 0.442 2.040 NaN NaN
forest winter 2019 1.000 0.059 0.267 0.387 2.002 0.520 2.682
baseline all 0.986 0.062 0.431 0.485 2.564 NaN NaN
forest all 0.990 0.062 0.328 0.422 2.184 0.508 2.659

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.982 0.097 0.421 0.482 2.125 NaN NaN
elr winter 2016 0.976 0.065 0.390 0.501 1.762 0.591 3.338
baseline winter 2017 0.983 0.028 0.487 0.536 2.285 NaN NaN
elr winter 2017 0.974 0.028 0.517 0.529 2.666 0.581 3.431
baseline winter 2018 0.986 0.068 0.459 0.484 2.564 NaN NaN
elr winter 2018 0.993 0.068 0.442 0.491 2.411 0.601 4.038
baseline winter 2019 0.993 0.059 0.361 0.442 2.040 NaN NaN
elr winter 2019 1.000 0.059 0.400 0.476 2.075 0.573 3.537
baseline all 0.986 0.062 0.431 0.485 2.564 NaN NaN
elr all 0.986 0.055 0.434 0.499 2.666 0.587 3.591

Extended logistic regression plots

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