code: def __init__(
      self,
      dataset_name,
      configuration_space,
      meta_base,
      logger,
      distance="l1",
      seed=None,
      use_features=None,
      distance_kwargs=None,
  ):
      self.dataset_name = dataset_name
      self.configuration_space = configuration_space
      self.meta_base = meta_base
      self.distance = distance
      self.seed = seed
      self.use_features = use_features
      self.distance_kwargs = distance_kwargs
      self.kND = None  # For caching, makes things faster...
  
      self.logger = logger
  
file_path: auto-sklearn/autosklearn/metalearning/optimizers/metalearn_optimizer/metalearner.py
imports: import ast
  import numpy
  import pandas
  import sklearn.utils
  from autosklearn.metalearning.metalearning.kNearestDatasets.kND import KNearestDatasets
label_desc: Use image node_id 1 to create a new MetaLearningOptimizer object from inherited base classes: object with example: obj = MetaLearningOptimizer(dataset_name, configuration_space, meta_base, logger, distance, seed, use_features, distance_kwargs)