Comments (2)
Hi @candalfigomoro by positive constraint, did you mean to make the predictions always positive? You could specify "min_admissible_value" in "SimpleSilverkiteTemplate.custom" and all negative values will be masked with 0.
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Thank you
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Related Issues (20)
- problems with additional regressors in low-level template HOT 1
- Different Precision Causes IndexError HOT 2
- pip3 install fail, osqp HOT 3
- Does multi-stage forecasting supports weekly aggregation as-well HOT 4
- Greykite Forecaster Model is Unpickle-able HOT 7
- Multivariate Support
- How to extract future trend? HOT 1
- support python 3.10 HOT 5
- No seasonal terms are included with seasonality options set to 'auto' with monthly data
- Forecasts appear too smooth for dataset original variability HOT 1
- can t set time col in metadata HOT 1
- Parallel execution on Spark, HOT 2
- ResourceWarning: Unclosed file... messages when deserializing a model. HOT 1
- The default performance of greykite silverkite is far worse than default prophet HOT 3
- Enforcing positive output, or how to tell the model not to produce negative results HOT 1
- Regressors Already Forecastd, No Lag Needed. But, getting AttributeError: 'dict' object has no attribute 'lagged_regressors' HOT 7
- Greykite feature scaling HOT 6
- Support for pandas 1.3 HOT 2
- Training the model on all data after benchmarking HOT 2
- regularization_strength Default value HOT 1
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