Comments (1)
I think the problem here is you are passing in df
as an arg to predict (which it sees as a positional arg for forecast length).
It is understandable you are trying to use the sklearn style but because there are more options here for data import there is a separate function to do that, model.fit_data(df)
.
In fact, there is no need to pickle AutoTS, you can simple model.export_template("your_file.csv", n=1)
then on a new AutoTS class:
model = AutoTS(...args)
model.import_best_model("your_file.csv")
model.fit_data(df)
model.predict()
from autots.
Related Issues (20)
- Limited Holiday Calendar Functionality in autots FBProphet for Time Series Prediction HOT 3
- model.predict gives different forecast depending on forecast_length HOT 5
- GluonTS not using all available (CPU) resources HOT 14
- Use only one variable as the target but supply many features to models. HOT 9
- Save best model for each serie instead of best model overall HOT 2
- Running out of RAM in 0.6.3 HOT 6
- adding autos package to https://repo.anaconda.com/pkgs/snowflake/ HOT 2
- In AutoTS class, custom dataframe is not being picked as initial_template HOT 2
- GluonTS model 'hangs' (on second template?) HOT 2
- Theta Template Eval Error HOT 3
- Fatal error on SeasonalityMotifImputer transformer HOT 2
- Additional metrics HOT 1
- AutoTS multiple variables HOT 5
- import_template erro Expecting value: line 1 column 1 (char 0) HOT 4
- support for forecast issue time HOT 1
- Supply Multiplevariate data to Predict() HOT 1
- Template Eval Error for most of the powerful and effective models HOT 3
- Error on HolidayTransformer since 0.6.12 HOT 3
- DMD template is in incorrect format and causes JSONDecoder exception. HOT 4
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from autots.