class_docstr: Defines the mixin for text explanations.
class_docstr_tok: ["Defines","the","mixin","for","text","explanations","."]
docstr: Get the feature importance values ordered by importance.
  
  This property exists for text explanations only and not for local because currently
  we are doing text explanations for a single document and it is more difficult to
  define order for multiple instances.  Note this is subject to change if we eventually
  add global explanations for text explainers.
  
  :return: For a model with a single output such as regression, this
      returns a list of feature importance values. For models with vector outputs this function
      returns a list of such lists, one for each output. The dimension of this matrix
      is (# examples x # features).
  :rtype: list
docstr_tok: ["Get","the","feature","importance","values","ordered","by","importance",".","This","property","exists","for","text","explanations","only","and","not","for","local","because","currently","we","are","doing","text","explanations","for","a","single","document","and","it","is","more","difficult","to","define","order","for","multiple","instances",".","Note","this","is","subject","to","change","if","we","eventually","add","global","explanations","for","text","explainers",".",":","return",":","For","a","model","with","a","single","output","such","as","regression",",","this","returns","a","list","of","feature","importance","values",".","For","models","with","vector","outputs","this","function","returns","a","list","of","such","lists",",","one","for","each","output",".","The","dimension","of","this","matrix","is","(","#","examples","x","#","features",")",".",":","rtype",":","list"]
code: def ordered_local_importance_values(self):
      """Get the feature importance values ordered by importance.
  
      This property exists for text explanations only and not for local because currently
      we are doing text explanations for a single document and it is more difficult to
      define order for multiple instances.  Note this is subject to change if we eventually
      add global explanations for text explainers.
  
      :return: For a model with a single output such as regression, this
          returns a list of feature importance values. For models with vector outputs this function
          returns a list of such lists, one for each output. The dimension of this matrix
          is (# examples x # features).
      :rtype: list
      """
      return self._ordered_local_importance_values
  
file_path: interpret-text/python/interpret_text/experimental/explanation.py
imports: import numpy
  import uuid
  from interpret_community.common.explanation_utils import _sort_values, _order_imp
  from interpret_community.common.constants import Dynamic, ExplanationParams, ExplainParams
  from interpret_community.explanation.explanation import LocalExplanation, ExpectedValuesMixin, ClassesMixin
label_desc: Use image node_id 4 for calling the TextExplanation obj's underlying member method code with example usage: obj.ordered_local_importance_values() and returns: self