dialoguekit.nlu.models.satisfaction_classifier
==============================================

.. py:module:: dialoguekit.nlu.models.satisfaction_classifier

.. autoapi-nested-parse::

   Satisfaction classification.

   The SVM model and data it was trained on are based on:
   https://github.com/sunnweiwei/user-satisfaction-simulation



Classes
-------

.. autoapisummary::

   dialoguekit.nlu.models.satisfaction_classifier.SatisfactionClassifier
   dialoguekit.nlu.models.satisfaction_classifier.SatisfactionClassifierSVM


Module Contents
---------------

.. py:class:: SatisfactionClassifier

   Bases: :py:obj:`abc.ABC`


   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:method:: classify_text(dialogue_text: Union[str, List[str]]) -> Union[int, List[int]]
      :abstractmethod:


      Classifies text.

      Allows for both list of string and a single string.

      :param dialogue_text: Text to be classified.

      :returns: If the provided input is a list, a list will be returned.
                If the input is a string, the return will be a single int.



   .. py:method:: classify_last_n_dialogue(dialogue: dialoguekit.core.dialogue.Dialogue, last_n: Optional[Union[int, None]] = None) -> int
      :abstractmethod:


      Classifies the last n utterances in a dialogue.

      If `last_n` is None the whole dialogue will be classified.

      :param dialogue: Dialogue to classify.
      :param last_n: How many of the last utterances in the dialogue to use for
                     the classification. Defaults to None.

      :raises TypeError: If `last_n` is greater then the length of the dialogue.

      :returns: Satisfaction classification.



.. py:class:: SatisfactionClassifierSVM

   Bases: :py:obj:`SatisfactionClassifier`


   SVM Satisfaction classifier.

   The SVM model is pre-trained on the English data from:
   https://github.com/sunnweiwei/user-satisfaction-simulation

   It classifies the users overall satisfaction with the system. Based on
   the agents responses to the user.

   The scale:
       1: Very dissatisfied
       2: Dissatisfied
       3: Normal
       4: Satisfied
       5: Very Satisfied


   .. py:method:: classify_text(dialogue_text: Union[str, List[str]]) -> Union[int, List[int]]

      Classifies satisfaction.

      :param dialogue_text: Text to classify.

      :returns: The classification score to the utterances.



   .. py:method:: classify_last_n_dialogue(dialogue: dialoguekit.core.dialogue.Dialogue, last_n: Optional[Union[int, None]] = None) -> int

      Classifies the n last dialogues.

      :param dialogue: Dialogue object to classify.
      :param last_n: Number of the last utterances to use for classification.
                     Defaults to None.

      :returns: Classification score.