Родитель
072824f284
Коммит
252882df96
Двоичные данные
assets/time_series_split_multiround.jpg
Двоичные данные
assets/time_series_split_multiround.jpg
Двоичный файл не отображается.
До Ширина: | Высота: | Размер: 79 KiB После Ширина: | Высота: | Размер: 125 KiB |
Двоичные данные
assets/time_series_split_singleround.jpg
Двоичные данные
assets/time_series_split_singleround.jpg
Двоичный файл не отображается.
До Ширина: | Высота: | Размер: 38 KiB После Ширина: | Высота: | Размер: 52 KiB |
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@ -160,11 +160,7 @@
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"\n",
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"Splitting time series data into a single round of trainig and testing data:\n",
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"![Single split](../../assets/time_series_split_singleround.jpg)\n",
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"\n",
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"\n",
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"\n",
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"Splitting time series data into a multi round of trainig and testing data (for cross-validation):\n",
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"![Multi split](../../assets/time_series_split_multiround.jpg)"
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"\n"
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]
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},
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{
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@ -1112,6 +1108,12 @@
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"We can also create training data and test data for multi-round forecasting. In this case, we gradually increase the length of the training data at each round. Note that the forecasting period we generate in each round are non-overlapping. This allows us to retrain the forecasting model for achieving more accurate forecasts. Using the settings defined in the **Parameters** section above, and updating `N_SPLITS` to `10`, we can generate the training and test sets as follows:\n",
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"\n",
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"\n",
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"\n",
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"\n",
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"Splitting time series data into a multi round of trainig and testing data (for cross-validation):\n",
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"![Multi split](../../assets/time_series_split_multiround.jpg)\n",
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"\n",
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"\n",
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"| **Round** | **Train period <br> start week** | **Train period <br> end week** | **Test period <br> start week** | **Test period <br> end week** |\n",
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"| -------- | --------------- | ------------------ | ------------------------- | ----------------------- |\n",
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"| 1 | 40 | 135 | 137 | 138 |\n",
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