class_docstr: Produces explanation specific to regression metrics.
class_docstr_tok: ["Produces","explanation","specific","to","regression","metrics","."]
docstr: Provides specific explanation data.
  
  Args:
      key: A number/string that references a specific data item.
  
  Returns:
      A serializable dictionary.
docstr_tok: ["Provides","specific","explanation","data",".","Args",":","key",":","A","number\/string","that","references","a","specific","data","item",".","Returns",":","A","serializable","dictionary","."]
code: def data(self, key=None):
      """Provides specific explanation data.
  
      Args:
          key: A number/string that references a specific data item.
  
      Returns:
          A serializable dictionary.
      """
      if key is None:
          return self._internal_obj["overall"]
      return None
  
file_path: interpret/python/interpret-core/interpret/perf/_regression.py
imports: from ..api.base import ExplainerMixin, ExplanationMixin
  from ..utils._explanation import gen_name_from_class
  from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score
  import numpy
  from ..utils._clean_x import preclean_X
  from ..utils._clean_simple import clean_dimensions
  from ..utils._unify_predict import determine_classes, unify_predict_fn
  from ..utils._unify_data import unify_data
label_desc: Use image node_id 2 for calling the RegressionExplanation obj's underlying member method code with example usage: obj.data(key) and returns: None, self