class_docstr: Generalized Linear Rule Model explainer. Provides access to the following
  directly interpretable supervised learning methods:
  
  * **Linear Rule Regression:** linear regression on rule-based features [#Icml2019]_.
  * **Logistic Rule Regression:** logistic regression on rule-based features [#Icml2019]_.
  
  References:
      .. [#Icml2019] `D. Wei, S. Dash, T. Gao, O. Günlük, "Generalized linear rule
         models." International Conference on Machine Learning (ICML), 2019.
         <http://proceedings.mlr.press/v97/wei19a/wei19a.pdf>`_
docstr: Initialize a GLRMExplainer object.
  
  Args:
    model: model to operate on. Instance of either
  
      * :class:`aix360.algorithms.rbm.linear_regression.LinearRuleRegression` or
      * :class:`aix360.algorithms.rbm.logistic_regression.LogisticRuleRegression`
code: def __init__(self, model):
      """
      Initialize a GLRMExplainer object.
  
      Args:
        model: model to operate on. Instance of either
  
          * :class:`aix360.algorithms.rbm.linear_regression.LinearRuleRegression` or
          * :class:`aix360.algorithms.rbm.logistic_regression.LogisticRuleRegression`
      """
      super(GLRMExplainer, self).__init__()
      self._model = model
  
file_path: AIX360/aix360/algorithms/rbm/GLRM.py
imports: from ..dise import DISExplainer
label_desc: Use image node_id 1 to create a new GLRMExplainer object from inherited base classes: DISExplainer with example: obj = GLRMExplainer(model)