ontolearn.learners.spell
========================

.. py:module:: ontolearn.learners.spell

.. autoapi-nested-parse::

   SPELL Learner - SAT-based concept learning using SPELL fitting.



Classes
-------

.. autoapisummary::

   ontolearn.learners.spell.SPELL


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

.. py:class:: SPELL(knowledge_base: ontolearn.abstracts.AbstractKnowledgeBase, reasoner: Optional[owlapy.abstracts.AbstractOWLReasoner] = None, max_runtime: Optional[int] = 60, max_query_size: int = 10, starting_query_size: int = 1, search_mode: str = 'full_approx')

   Bases: :py:obj:`ontolearn.learners.sat_base.SATBaseLearner`


   SPELL: SAT-based concept learner using general SPELL fitting.

   This learner uses SAT solvers to find concept expressions that fit positive and negative examples.
   Unlike ALCSAT which is specialized for ALC, SPELL uses the more general fitting.py module
   which supports different modes of operation.

   The algorithm incrementally searches for queries of increasing size that maximize
   the coverage on the given examples.

   .. attribute:: kb

      The knowledge base that the concept learner is using.

      :type: AbstractKnowledgeBase

   .. attribute:: max_query_size

      Maximum size of queries to search for.

      :type: int

   .. attribute:: search_mode

      Search mode - exact, neg_approx, or full_approx.

   .. attribute:: _best_hypothesis

      Best found hypothesis.

      :type: OWLClassExpression

   .. attribute:: _best_hypothesis_accuracy

      Accuracy of the best hypothesis.

      :type: float

   .. attribute:: _structure

      Internal structure representation of the knowledge base.

      :type: Structure

   .. attribute:: _ind_to_owl

      Mapping from internal individual indices to OWL individuals.

      :type: dict

   .. attribute:: _owl_to_ind

      Mapping from OWL individuals to internal indices.

      :type: dict


   .. py:attribute:: __slots__
      :value: ('max_query_size', 'starting_query_size', 'search_mode')



   .. py:attribute:: name
      :value: 'spell'



   .. py:attribute:: max_query_size
      :value: 10



   .. py:attribute:: starting_query_size
      :value: 1



   .. py:attribute:: search_mode


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

      Find concept expressions that explain positive and negative examples.

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

      :returns: self