autots.templates package¶
Submodules¶
autots.templates.general module¶
Starting templates for models.
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autots.templates.general.
general_template
= Model ... Ensemble 0 ARIMA ... 0 1 ARIMA ... 0 2 ARIMA ... 0 3 ARIMA ... 0 4 ARIMA ... 0 5 AverageValueNaive ... 0 6 AverageValueNaive ... 0 7 AverageValueNaive ... 0 8 DatepartRegression ... 0 9 DatepartRegression ... 0 10 DatepartRegression ... 0 11 DatepartRegression ... 0 12 ETS ... 0 13 ETS ... 0 14 GLM ... 0 15 GLM ... 0 16 GLS ... 0 17 GLS ... 0 18 GluonTS ... 0 19 GluonTS ... 0 20 GluonTS ... 0 21 GluonTS ... 0 22 GluonTS ... 0 23 GluonTS ... 0 24 LastValueNaive ... 0 25 LastValueNaive ... 0 26 LastValueNaive ... 0 27 LastValueNaive ... 0 28 SeasonalNaive ... 0 29 SeasonalNaive ... 0 30 SeasonalNaive ... 0 31 SeasonalNaive ... 0 32 UnobservedComponents ... 0 33 UnobservedComponents ... 0 34 UnobservedComponents ... 0 35 VAR ... 0 36 VAR ... 0 37 VAR ... 0 38 VECM ... 0 39 VECM ... 0 40 VECM ... 0 41 VECM ... 0 42 WindowRegression ... 0 43 ZeroesNaive ... 0 [44 rows x 4 columns]¶ # Basic Template Construction Code # transformer_max_depth = 6 and transformer_list = “fast” from autots.evaluator.auto_model import unpack_ensemble_models max_per_model_class = 1 export_template = model.validation_results.model_results export_template = export_template[
export_template[‘Runs’] >= (model.num_validations + 1)
] export_template = (
export_template.sort_values(‘Score’, ascending=True) .groupby(‘Model’) .head(max_per_model_class) .reset_index()
) import json export2 = unpack_ensemble_models(model.best_model, keep_ensemble=False, recursive=True) export_final = pd.concat([export_template, export2]) export_final = export_final[export_final[‘Ensemble’] < 1] export_final[[“Model”, “ModelParameters”, “TransformationParameters”, “Ensemble”]].reset_index(drop=True).to_json(orient=’index’)
Module contents¶
Model Templates