ontolearn.quality_funcs
=======================

.. py:module:: ontolearn.quality_funcs


Functions
---------

.. autoapisummary::

   ontolearn.quality_funcs.f1
   ontolearn.quality_funcs.acc
   ontolearn.quality_funcs.evaluate_concept


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

.. py:function:: f1(*, individuals: Set, pos: Set, neg: Set)

.. py:function:: acc(*, individuals: Set, pos: Set, neg: Set)

.. py:function:: evaluate_concept(kb: ontolearn.abstracts.AbstractKnowledgeBase, concept: owlapy.class_expression.OWLClassExpression, quality_func: ontolearn.abstracts.AbstractScorer, encoded_learning_problem: ontolearn.abstracts.EncodedLearningProblem) -> ontolearn.search.EvaluatedConcept

   Evaluates a concept by using the encoded learning problem examples, in terms of Accuracy or F1-score.

   .. note::

      This method is useful to tell the quality (e.q) of a generated concept by the concept learners, to get
      the set of individuals (e.inds) that are classified by this concept and the amount of them (e.ic).

   :param kb: The knowledge base where to evaluate the concept.
   :param concept: The concept to be evaluated.
   :param quality_func: Quality measurement in terms of Accuracy or F1-score.
   :param encoded_learning_problem: The encoded learning problem.

   :returns: The evaluated concept.