ontolearn.learners.ocel
Classes
A limited version of CELOE. |
Module Contents
- class ontolearn.learners.ocel.OCEL(knowledge_base: KnowledgeBase, reasoner: owlapy.abstracts.AbstractOWLReasoner | None = None, refinement_operator: BaseRefinement[OENode] | None = None, quality_func: AbstractScorer | None = None, heuristic_func: AbstractHeuristic | None = None, terminate_on_goal: bool | None = None, iter_bound: int | None = None, max_num_of_concepts_tested: int | None = None, max_runtime: int | None = None, max_results: int = 10, best_only: bool = False, calculate_min_max: bool = True)[source]
Bases:
ontolearn.learners.celoe.CELOE
A limited version of CELOE.
- best_descriptions
Best hypotheses ordered.
- Type:
EvaluatedDescriptionSet[OENode, QualityOrderedNode]
- best_only
If False pick only nodes with quality < 1.0, else pick without quality restrictions.
- Type:
bool
- calculate_min_max
Calculate minimum and maximum horizontal expansion? Statistical purpose only.
- Type:
bool
- heuristic_func
Function to guide the search heuristic.
- Type:
- iter_bound
Limit to stop the algorithm after n refinement steps are done.
- Type:
int
- kb
The knowledge base that the concept learner is using.
- Type:
- max_child_length
Limit the length of concepts generated by the refinement operator.
- Type:
int
- max_he
Maximal value of horizontal expansion.
- Type:
int
- max_num_of_concepts_tested
- Type:
int
- max_runtime
Limit to stop the algorithm after n seconds.
- Type:
int
- min_he
Minimal value of horizontal expansion.
- Type:
int
- name
Name of the model = ‘ocel_python’.
- Type:
str
- _number_of_tested_concepts
Yes, you got it. This stores the number of tested concepts.
- Type:
int
- operator
Operator used to generate refinements.
- Type:
- quality_func
- Type:
- reasoner
The reasoner that this model is using.
- Type:
AbstractOWLReasoner
- search_tree
Dict to store the TreeNode for a class expression.
- start_class
The starting class expression for the refinement operation.
- Type:
OWLClassExpression
- start_time
The time when
fit()
starts the execution. Used to calculate the total timefit()
takes to execute.- Type:
float
- terminate_on_goal
Whether to stop the algorithm if a perfect solution is found.
- Type:
bool
- __slots__ = ()
- name = 'ocel_python'