class_docstr: An 'Auto Regressive Integrated (Random) Forest'
class_docstr_tok: ["An","'Auto","Regressive","Integrated","(","Random",")","Forest","'"]
docstr: Parameters:
  -----------
  
  order: int
      the order of the 'autoregressiveness'
  diff_order: int
      the differencing order used
      TODO: Not used so far!
docstr_tok: ["Parameters",":","--","--","--","--","--","-","order",":","int","the","order","of","the","'autoregressiveness'","diff_order",":","int","the","differencing","order","used","TODO",":","Not","used","so","far","!"]
code: def __init__(self, order=2, diff_order=0):
      """
      Parameters:
      -----------
  
      order: int
          the order of the 'autoregressiveness'
      diff_order: int
          the differencing order used
          TODO: Not used so far!
      """
      self.order = order
      self.diff_order = diff_order
  
file_path: HpBandSter/hpbandster/optimizers/learning_curve_models/arif.py
imports: import sys
  import numpy
  from sklearn.ensemble import RandomForestRegressor
  from hpbandster.learning_curve_models.base import LCModel
  from IPython import embed
label_desc: Use image node_id 1 to create a new ARIF object from inherited base classes: lcm_base with example: obj = ARIF(order, diff_order)