class_docstr: Create grouped estimators based on passed estimator
code: def __init__(self, estimator, grouped):
      if not isinstance(grouped, pd.core.groupby.DataFrameGroupBy):
          raise ValueError(
              "'grouped' must be DataFrameGroupBy instance"
          )
  
      import sklearn.base as base
  
      self.groups = {}
  
      for name, group in grouped:
          e = base.clone(estimator)
          e = e.set_params(**estimator.get_params())
          self.groups[name] = e
  
imports: import pandas
  import pandas.compat
  from pandas_ml.compat import Appender
  from pandas_ml.core.base import _BaseEstimator
  from pandas_ml.core.frame import ModelFrame
  from pandas_ml.core.generic import ModelPredictor, _shared_docs
  from pandas_ml.core.series import ModelSeries
label_desc: Use image node_id 1 to create a new GroupedEstimator object from inherited base classes: _BaseEstimator with example: obj = GroupedEstimator(estimator, grouped)