autots.templates package

Submodules

autots.templates.general module

Starting templates for models.

autots.templates.general.general_template = Model  ... Ensemble 1                ARIMA  ...        0 3    AverageValueNaive  ...        0 4    AverageValueNaive  ...        0 5    AverageValueNaive  ...        0 6   DatepartRegression  ...        0 ..                 ...  ...      ... 71           Cassandra  ...        0 72      NeuralForecast  ...        0 73           Cassandra  ...        0 74                 DMD  ...        0 75                 DMD  ...        0  [74 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’)

import pprint import json

imported = pd.read_csv(“autots_forecast_template_gen.csv”) export = unpack_ensemble_models(imported, keep_ensemble=False, recursive=True) export[export[‘Ensemble’] < 1].to_json(“template.json”, orient=”records”) with open(“template.json”, “r”) as jsn:

json_temp = json.loads(jsn.read())

print(json_temp) with open(“template.txt”, “w”) as txt:

txt.write(json.dumps(json_temp, indent=4, sort_keys=False))

Module contents

Model Templates