ontolearn.learners.sat_base
===========================

.. py:module:: ontolearn.learners.sat_base

.. autoapi-nested-parse::

   Base class for SAT-based concept learners.



Classes
-------

.. autoapisummary::

   ontolearn.learners.sat_base.SATBaseLearner


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

.. py:class:: SATBaseLearner(knowledge_base: ontolearn.abstracts.AbstractKnowledgeBase, reasoner: Optional[owlapy.abstracts.AbstractOWLReasoner] = None, max_runtime: Optional[int] = 60, cache_structure: bool = True)

   Base class for SAT-based concept learners that use the SPELL framework.

   This class provides common functionality for converting between OWL ontologies
   and the Structure format used by SPELL, as well as converting results back to
   OWL class expressions.


   .. py:attribute:: __slots__
      :value: ('kb', 'reasoner', 'max_runtime', '_best_hypothesis', '_best_hypothesis_accuracy',...



   .. py:attribute:: kb


   .. py:attribute:: reasoner
      :value: None



   .. py:attribute:: max_runtime
      :value: 60



   .. py:attribute:: cache_structure
      :value: True



   .. py:attribute:: start_time
      :value: None



   .. py:method:: clean()

      Clear all states of the concept learner.



   .. py:method:: fit(lp: ontolearn.learning_problem.PosNegLPStandard)
      :abstractmethod:


      Find concept expressions that explain positive and negative examples.

      :param lp: Learning problem with positive and negative examples.

      :returns: self



   .. py:method:: best_hypothesis() -> owlapy.class_expression.OWLClassExpression

      Get the best found hypothesis.

      :returns: OWL class expression, or OWLThing if no hypothesis found.



   .. py:method:: best_hypothesis_accuracy() -> Optional[float]

      Get the accuracy of the best found hypothesis.

      :returns: Accuracy as float, or None if no hypothesis found.