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Introduced post processing #937
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@@ -81,6 +81,13 @@ def _train_model(self, i, series_id, df, model_kwargs): | |||
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data = self.preprocess(df, series_id) | |||
cap = data['y'].max() * 1.2 |
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Do we need to have a cap?
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Yes, It's mandatory with logistic growth function. Removed logistic growth function for now as it fails during generating local explanations.
if self.spec.postprocessing.enabled: | ||
floor = self.spec.postprocessing.steps.set_min_forecast | ||
else: | ||
floor = data['y'].min() * 0.8 |
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Shouldn't we leave this to the framework? Why 0,8?
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It's mandatory with logistic growth function. Removed logistic growth function for now.
@@ -317,6 +317,25 @@ spec: | |||
required: false | |||
default: false | |||
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postprocessing: |
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This is a great way to add it 👍
…res to manage evaluation service configurations.
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ODSC-61573
Following schema can be used to set min value for the forecast value