class_docstr: An 'Auto Regressive Integrated (Random) Forest'
class_docstr_tok: ["An","'Auto","Regressive","Integrated","(","Random",")","Forest","'"]
code: def apply_differencing(self, series, order=None):
      if order is None:
          order = self.diff_order
  
      for o in range(order):
          series = series[1:] - series[:-1]
      return series
  
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 2 for calling the ARIF obj's underlying member method code with example usage: obj.apply_differencing(series, order) and returns: series