Update DeepAR to generate prediction intervals
#761
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Codecov Report
@@ Coverage Diff @@
## master #761 +/- ##
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+ Coverage 83.50% 83.54% +0.03%
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Files 122 122
Lines 6748 6764 +16
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+ Hits 5635 5651 +16
Misses 1113 1113
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martins0n
suggested changes
Jun 20, 2022
etna/models/nn/deepar.py
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| from typing import Union | ||
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| import pandas as pd | ||
| from pytorch_forecasting.metrics import DistributionLoss |
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We should move it to if SETTINGS.torch_required: block
martins0n
suggested changes
Jun 20, 2022
| for segment in forecast.segments: | ||
| segment_slice = forecast[:, segment, :][segment] | ||
| assert {"target_0.025", "target_0.975", "target"}.issubset(segment_slice.columns) | ||
| assert (segment_slice["target_0.975"] - segment_slice["target_0.025"] >= 0).all() |
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Let's add checks if mean lower-greater than quantiles
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Before submitting (must do checklist)
Type of Change
Proposed Changes
Look #738.
Related Issue
#738.
Closing issues
Closes #738.