GMS location: 458

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.976 0.087 0.354 0.438 2.635 NaN NaN
forest winter 2016 0.988 0.130 0.322 0.403 2.839 0.486 6.973
baseline winter 2017 0.980 0.025 0.356 0.422 2.076 NaN NaN
forest winter 2017 0.980 0.025 0.274 0.360 1.810 0.451 3.757
baseline winter 2018 0.984 0.097 0.271 0.376 2.159 NaN NaN
forest winter 2018 0.984 0.097 0.234 0.335 2.288 0.458 3.518
baseline winter 2019 1.000 0.062 0.261 0.398 1.620 NaN NaN
forest winter 2019 1.000 0.062 0.227 0.363 1.449 0.444 2.854
baseline all 0.984 0.064 0.314 0.410 2.635 NaN NaN
forest all 0.988 0.073 0.269 0.368 2.839 0.462 4.492

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.976 0.087 0.354 0.438 2.635 NaN NaN
elr winter 2016 0.982 0.087 0.381 0.459 2.396 0.615 7.144
baseline winter 2017 0.980 0.025 0.356 0.422 2.076 NaN NaN
elr winter 2017 0.971 0.025 0.324 0.400 1.791 0.506 4.694
baseline winter 2018 0.984 0.097 0.271 0.376 2.159 NaN NaN
elr winter 2018 0.984 0.129 0.261 0.360 2.337 0.534 3.910
baseline winter 2019 1.000 0.062 0.261 0.398 1.620 NaN NaN
elr winter 2019 1.000 0.125 0.257 0.387 1.761 0.474 3.074
baseline all 0.984 0.064 0.314 0.410 2.635 NaN NaN
elr all 0.984 0.082 0.311 0.406 2.396 0.540 4.904

Extended logistic regression plots

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