mlforecast
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Scalable machine 🤖 learning for time series forecasting.
Hi, It would be nice if it was possible to configure the following pipeline : - Create from a target (or other data) a bunch of features (from domain knowledge...
## Description This PR allows training [Cycling Boostin Machines](CBM). Requested in #127. Checklist: - [ ] This PR has a meaningful title and a clear description. - [ ] The...
### What happened + What you expected to happen Didn't see a specific page for submitting issues about the tutorials. https://nixtlaverse.nixtla.io/mlforecast/docs/tutorials/electricity_load_forecasting.html In the Test Evaluation section, `df_train` is still being...
### Description The current version of MLForecast does not support applying custom weights during cross-validation training. The custom training feature described in the documentation is only available for the final...
### What happened + What you expected to happen I am unable to get the basic script in the repo README to work. In JupyterLab running in VS Studio, the...
### What happened + What you expected to happen Hello, I am using MLforecast, specifically xgboost for a forecasting task. Recently I have found that the same code and data...
### Description We currently don't check that the dates in the dataframe provided to the update method are actually in the future, so users could append already seen values, we...
### Description Currently, the prediction intervals can only be generated using the two provided methods (conformal_distribution & conformal_error). Extending this functionality to custom prediction interval methods would greatly extend the...
### Description Currently when you use `MLForecast.forecast_fitted_values()` it only can produce one-step ahead predictions on the training set without the ability to customize the horizon. It would be great if...
### What happened + What you expected to happen Lag features are returning nulls when they should not be, the issue appears to only affect the distributed forecast module. Running...