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0.5.0

Added
- Added confidence intervals using bootstrapping
- `set_cilvel()` function (default .95)
- `set_bootstrap_samples()` function (default 100)
- Added `ci` parameter to `plot()` and `plot_test_set()` function
- Added UpperCI, LowerCI, TestSetUpperCI, TestSetLowerCI keys to history dict
- Added `export_forecasts_with_cis()` and `export_test_set_preds_with_cis()` functions
- Added source code (commented out) to get level confidence intervals -- when I tested, the intervals were too large to implement but maybe in the future this will be revisited
Changed
Fixed

0.4.25

Added
Changed
Fixed
- source code was using `f` instead of `self` when when calling `pop_using_criterion()`

0.4.4

Added
- added lstm grid in example grids
- added EarlyStopping callback functionality for the LSTM model
- added `get_expanded_lstm_grid()` to GridGenerator module which gives an example of a grid with early stopping
Changed
- changed default paramaters for the lstm model
- added `**kwargs` to the lstm model forecast function that are passed to the `fit()` function in TensorFlow, got rid of `epochs` and `batch_size` args consequently
Fixed

0.4.2

Added
- lstm estimator
- added `pop_using_criterion()` function
Changed
- Fixed an issue where sklearn models were being fit on the same data twice -- does not change outcomes but the models run faster now
- Output from `_scale()` function is now always a numpy matrix (could have been either that or pandas dataframe before)
- sorted `_estimators_` list
- changed the error message for when importing a grid fails to account for one other possible reason the failure occured
Fixed

0.4.1

Added
- Can now sort by metric value in `export_all_validation_grids_to_excel()`
Changed
Fixed
- Fixed an issue where sometimes the incorrect AR terms were being propogated for test-set evaluation only

0.4.0

Added
Changed
- deleted the 'scale' normalizer from the mlp grid
Fixed
- Fixed an issue with the PowerTransformer normalizer that failed because of a DivideByZero error, now defaults to a StandardScaler when this issue is encountered and logs a warning

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