program: rnn_sweep.py
method: bayes
project: integer-sequence
name: Finding best hyperparameters for price prediction
early_terminate:
  type: hyperband
  min_iter: 2000
metric:
  goal: maximize
  name: accuracy_test
parameters:
    path : 'data/'
    sliding_window_size: 
      values:
        - 90
        - 150
        - 365
        - 730
      distribution: categorical
    retrain_every: 
      values:
        - 7
        - 14
        - 30
        - 60
      distribution: categorical
    scaler: 'minmax' # 'normalize' 'minmax' 'standardize' 'none'
    include_original_data_in_ensemble: True
    method: 
      values:
        - 'classification'
        - 'regression'
      distribution: categorical
    forecasting_horizon: 
      value: 1
      distribution: constant