dialoguekit.nlu.models.intent_classifier_cosine
===============================================

.. py:module:: dialoguekit.nlu.models.intent_classifier_cosine

.. autoapi-nested-parse::

   Implements intent classification based on cosine similarity.



Classes
-------

.. autoapisummary::

   dialoguekit.nlu.models.intent_classifier_cosine.IntentClassifierCosine


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

.. py:class:: IntentClassifierCosine(intents: List[dialoguekit.core.intent.Intent])

   Bases: :py:obj:`dialoguekit.nlu.intent_classifier.IntentClassifier`


   Cosine Intent classifier.

   :param intents: Allowed intents.


   .. py:method:: train_model(utterances: List[dialoguekit.core.utterance.Utterance], labels: List[dialoguekit.core.intent.Intent]) -> None

      Trains a model based on a set of labeled utterances.

      :param utterances: List of Utterance instances.
      :param labels: List of associated intent labels.



   .. py:method:: classify_intent(utterance: dialoguekit.core.utterance.Utterance) -> dialoguekit.core.intent.Intent

      Classifies the utterances intent.

      Classifies the intent of an utterance based on based cosine
      similarity of TF-IDF-weighted term vectors.

      :param utterance: An utterance.

      :returns: Predicted intent.



   .. py:method:: save_model(file_path: str) -> None

      Saves the trained model to a file.

      This method uses the joblib library to save the model.

      :param file_path: File path.



   .. py:method:: load_model(file_path: str) -> None

      Loads a model from a file.

      This method uses the joblib library to load the model.

      :param file_path: File path.