finnts 0.2.0
Improvements
- Added spark support to run Finn in parallel on Azure Databricks or
Azure Synapse.
- Added error handling when creating simple model averages. Should
allow forecast to keep running even if there are memory issues when
averaging individual forecast models, which helps on large data
sets.
- Expand Azure Batch task timeout from one day to one week. Prevents
errors when running large forecasts that take over a day to run in Azure
Batch.
Deprecated
- Deprecated azure_batch parallel compute option within
forecast_time_series function since the Azure Batch R packages are
deprecated. Please use the new integration with spark on Azure.
finnts 0.1.1
Default Function Behavior
- Change default behavior to only run R1 feature engineering recipe
when the argument run_global_models is set to TRUE or NULL and
recipes_to_run is set to NULL in the forecast_time_series function.
Running R2 recipe with global models on large data sets often results in
RAM issues when running in Azure Batch.
Bug Fixes
- Fixed error when converting infinite values to NA values after model
forecasts are created.
- Changed the cubist model to reference the new cubist model
definition in parsnip package.
- Fixed bug in hierarchical forecasting. Missing values in the
hierarchy are converted from NA to zero, which fixes how data is
aggregated at various levels of hierarchy.
finnts 0.1.0