:py:mod:`ontolearn.experiments`
===============================

.. py:module:: ontolearn.experiments

.. autoapi-nested-parse::

   Experiments to validate a concept learning model.



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

Classes
~~~~~~~

.. autoapisummary::

   ontolearn.experiments.Experiments




.. py:class:: Experiments(max_test_time_per_concept=3)


   .. py:method:: store_report(model, learning_problems: List[Iterable], test_report: List[dict]) -> Tuple[str, Dict[str, Any]]
      :staticmethod:

      Create a report for concepts generated for a particular learning problem.
      :param model: Concept learner.
      :param learning_problems: A list of learning problems (lps) where lp corresponds to target concept, positive and
                                negative examples, respectively.
      :param test_report: A list of predictions (preds) where test_report => { 'Prediction': str, 'F-measure': float,
                          'Accuracy', 'Runtime':float}.

      :returns: Both report as string and report as dictionary.


   .. py:method:: start_KFold(k=None, dataset: List[Tuple[str, Set, Set]] = None, models: Iterable = None)

      Perform KFold cross validation.

      :param models: concept learners.
      :param k: k value of k-fold.
      :param dataset: A list of tuples where a tuple (i,j,k) where i denotes the target concept j denotes the set of
                      positive examples and k denotes the set of negative examples.

      .. note:: This method returns nothing. It just prints the report results.


   .. py:method:: start(dataset: List[Tuple[str, Set, Set]] = None, models: List = None)


   .. py:method:: report_results(results, num_problems)
      :staticmethod:

      Prints the result generated from validations.