The previous code now fails to infer test.
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 25/100
- Issue type
- Bug
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- azure, jupyter-notebook, python
- Domain
- cloud, machine-learning
Research direction
Start with the linked auto-ml-forecasting-function.ipynb tutorial and inspect how X_pred, forecast_destination, and the forecast horizon are configured. Reproduce the failure under Python 3.8 if possible, then verify that the tutorial either runs successfully or clearly documents the required forecast-date constraints.
Written by the indexing model from the issue text.
Description
- The error is below.What are the causes and solution?
AzureMLException: AzureMLException:
Message: Input prediction data X_pred or input forecast_destination contains dates later than the forecast horizon. Please shorten the prediction data so that it is within the forecast horizon or adjust the forecast_destination date.
InnerException None
ErrorResponse
{
"error": {
"code": "UserError",
"message": "Input prediction data X_pred or input forecast_destination contains dates later than the forecast horizon. Please shorten the prediction data so that it is within the forecast horizon or adjust the forecast_destination date.",
"target": "horizon",
"inner_error": {
"code": "BadData",
"inner_error": {
"code": "ForecastHorizonExceeded"
}
}
}
}
- python version is 3.8.
- The tutorial is below
https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb
- Dominant language
- Jupyter Notebook
- Stars
- 4.4k
- Forks
- 2.6k
- PR merge metrics
- No merged PRs in 30d
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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