FIX: Insample predictions with series of varying lengths #1246
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Jan 10, 2025
elephaint
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Feb 5, 2025
| @@ -37,7 +37,18 @@ | |||
| "execution_count": null, | |||
| "id": "515672ca", | |||
| "metadata": {}, | |||
| "outputs": [], | |||
| "outputs": [ | |||
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Please clear (not clean) notebooks
| @@ -1687,7 +1731,93 @@ | |||
| "execution_count": null, | |||
| "id": "4bede563-78c0-40ee-ba76-f06f329cd772", | |||
| "metadata": {}, | |||
| "outputs": [], | |||
| "outputs": [ | |||
| if test_size > 0 or forefront_offset > 0: | ||
| trimmed_dataset = TimeSeriesDataset.trim_dataset( | ||
| dataset=self.dataset, right_trim=test_size, left_trim=forefront_offset | ||
| for i in range(self.dataset.n_groups): |
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So we loop individually over all series?
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| # original y | ||
| # Combine all series forecasts DataFrames | ||
| if isinstance(fcsts_dfs[0], pl_DataFrame): |
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Can't we use ufp.concat here?
| " 'val_check_steps': 1,\n", | ||
| " 'step_size': 12}\n", | ||
| "\n", | ||
| "def get_expected_size(df, h, test_size, step_size):\n", |
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Difficult to disect but is this the unit test for having insample predictions with series of varying lengths? If not, do we have it?
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Currently,
predict_insample()assumes all series have the same length.This fix allows insample predictions with series of different lengths.