EmbeddingsRankBasedEvaluator

class mowl.evaluation.EmbeddingsRankBasedEvaluator(class_embeddings, testing_set, eval_method_class, score_func=None, training_set=None, relation_embeddings=None, head_entities=None, tail_entities=None, device='cpu')[source]

Bases: RankBasedEvaluator

This class corresponds to evaluation based on raking where the embedding information are just vectors and are not part of a model.

Parameters:

  • class_embeddings (dict(str, numpy.ndarray)) – The embeddings of the classes.

  • testing_set (list(mowl.projection.edge.Edge)) – Set of triples that are true positives.

  • eval_method_class (mowl.evaluation.base.EvaluationMethod) – Class that contains placeholders for class and relation embeddings.

  • score_func – The function used to compute the score. Defaults to None. This function will be inserted into the eval_method_class.

  • training_set (list(mowl.projection.edge.Edge)) – Set of triples that are true positives but exist in the training set. This is used to compute filtered metrics.

  • relation_embeddings (dict(str, numpy.ndarray), optional) – The embeddings of the relations. Defaults to None.

  • head_entities (list(str)) – List of entities that are used as head entities in the testing set.

  • tail_entities (list(str)) – List of entities that are used as tail entities in the testing set.

  • device (str) – Use cpu or cuda