class_docstr: An abstract base class for Label Graph clustering
  
  Inherit it in your classifier according to`developer guide <../developer.ipynb>`_.
class_docstr_tok: ["An","abstract","base","class","for","Label","Graph","clustering","Inherit","it","in","your","classifier","according","to","`","developer","guide","<","..","\/developer.ipynb",">","`","_","."]
docstr: Abstract method for clustering label space
  
  Implement it in your classifier according to`developer guide <../developer.ipynb>`_.
  
  Raises
  ------
  NotImplementedError
      this is an abstract method
docstr_tok: ["Abstract","method","for","clustering","label","space","Implement","it","in","your","classifier","according","to","`","developer","guide","<","..","\/developer.ipynb",">","`","_",".","Raises","--","--","--","NotImplementedError","this","is","an","abstract","method"]
code: def fit_predict(self, X, y):
      """Abstract method for clustering label space
  
      Implement it in your classifier according to`developer guide <../developer.ipynb>`_.
  
      Raises
      ------
      NotImplementedError
          this is an abstract method
      """
      raise NotImplementedError(
          "LabelGraphClustererBase::fit_predict()"
      )
  
file_path: scikit-multilearn/skmultilearn/cluster/base.py
imports: from builtins import object
  from ..utils import get_matrix_in_format
  from sklearn.base import BaseEstimator
label_desc: Use image node_id 2 for calling the LabelGraphClustererBase obj's underlying member method code with example usage: obj.fit_predict(X, y) without return types