code: def __init__(
      self,
      n_trees=50,
      max_depth=None,
      min_samples_split=1,
      max_monkeys=7,
      max_features="auto",
      n_jobs=1,
      random_state=None,
  ):
      self.n_trees = float(n_trees)
      self.max_depth = max_depth
      self.min_samples_split = min_samples_split
      self.max_features = max_features
      self.n_jobs = float(n_jobs)
      self.random_state = random_state
      self.rf = RandomForestRegressorWithVariance(
          n_estimators=n_trees,
          max_depth=max_depth,
          min_samples_split=min_samples_split,
          max_features=max_features,
          n_jobs=n_jobs,
          random_state=random_state,
      )
  
file_path: auptimizer/src/aup/Proposer/spearmint/chooser/RandomForestEIChooser.py
imports: import numpy
  import numpy.random
  import scipy.stats
  import sklearn.ensemble
  import sklearn.ensemble.forest
  from ..None import util
  import logging
  from sklearn.externals.joblib import Parallel, delayed
label_desc: Use image node_id 1 to create a new RandomForestEIChooser object  with example: obj = RandomForestEIChooser(n_trees, max_depth, min_samples_split, max_monkeys, max_features, n_jobs, random_state)