TBATSWrapper

class hcrystalball.wrappers.TBATSWrapper(use_box_cox=None, box_cox_bounds=(0, 1), use_trend=None, use_damped_trend=None, seasonal_periods=None, use_arma_errors=True, show_warnings=True, n_jobs=None, multiprocessing_start_method='spawn', context=None, name='TBATS', fit_params=None, conf_int=False, conf_int_level=0.95, clip_predictions_lower=None, clip_predictions_upper=None, hcb_verbose=True)[source]

Bases: hcrystalball.wrappers._tbats.BaseTBATSWrapper

Wrapper for TBATS model

https://github.com/intive-DataScience/tbats

Brings TBATS to sklearn time-series compatible interface and puts fit parameters to initialization stage.

Parameters
  • name (str) – Name of the model instance, used also as column name for returned prediction.

  • fit_params (dict) – Parameters passed to fit TBATS model.

  • conf_int (bool) – Whether confidence intervals should be also outputed.

  • conf_int_level (float) – Confidence level of returned confidence interval

  • clip_predictions_lower (float) – Minimal value allowed for predictions - predictions will be clipped to this value.

  • clip_predictions_upper (float) – Maximum value allowed for predictions - predictions will be clipped to this value.

  • hcb_verbose (bool) – Whtether to keep (True) or suppress (False) messages to stdout and stderr from the wrapper and 3rd party libraries during fit and predict

Notes

Fitting the model might take significant time. You might consider advices from the author https://medium.com/p/cf3e4e80cf48/responses/show

Methods Summary

fit(X, y)

Fit the model.

get_params([deep])

Get parameters for this estimator.

predict(X)

Transform data to tbats required format and run the predictions.

set_params(**params)

Set the parameters of this estimator.

Methods Documentation

fit(X, y)

Fit the model.

Parameters
  • X (pandas.DataFrame) – Input features.

  • y (array_like, (1d)) – Target vector.

Returns

Return type

self

get_params(deep=True)

Get parameters for this estimator.

Parameters

deep (bool, default=True) – If True, will return the parameters for this estimator and contained subobjects that are estimators.

Returns

params – Parameter names mapped to their values.

Return type

dict

predict(X)

Transform data to tbats required format and run the predictions.

Parameters

X (pandas.DataFrame) – Input features.

Returns

Prediction stored in column with name being the name of the wrapper.

Return type

pandas.DataFrame

set_params(**params)

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as Pipeline). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Parameters

**params (dict) – Estimator parameters.

Returns

self – Estimator instance.

Return type

estimator instance