cli-automl-forecasting-task-energy-demand.yml

$schema: https://azuremlsdk2.blob.core.windows.net/preview/0.0.1/autoMLJob.schema.json
type: automl

experiment_name: dpv2-cli-automl-forecasting-energy-demand
# name: dpv2-sdk-forecasting-train-job-01
description: A Time-Series Forecasting job using energy demand dataset
compute: azureml:cpu-cluster
task: forecasting
primary_metric: normalized_root_mean_squared_error
log_verbosity: info

training_data:
  path: "./training-mltable-folder"
  type: mltable

test_data:
  path: "./test-mltable-folder"
  type: mltable

target_column_name: demand
n_cross_validations: auto

limits:
  timeout_minutes: 20
  max_trials: 10
  max_concurrent_trials: 4
  trial_timeout_minutes: 20
  enable_early_termination: true

forecasting:
  time_column_name: "timeStamp"
  forecast_horizon: 48
  frequency: "H"
  target_lags: "auto"

training:
  enable_model_explainability: true
  enable_stack_ensemble: false
  blocked_training_algorithms: ["extreme_random_trees", "auto_arima", "prophet"]