mowl.models

Classes

ELBoxEmbeddings(dataset[, embed_dim, ...])

Implementation based on [peng2020].

ELBoxGDA(*args, **kwargs)

Example of ELBoxEmbeddings for gene-disease associations prediction.

ELBoxPPI(*args, **kwargs)

Example of ELBoxEmbeddings for protein-protein interaction prediction.

ELEmGDA(*args, **kwargs)

Example of ELEmbeddings for gene-disease associations prediction.

ELEmPPI(*args, **kwargs)

Example of ELEmbeddings for protein-protein interaction prediction.

ELEmbeddings(dataset[, embed_dim, margin, ...])

Implementation based on [kulmanov2019].

GraphPlusPyKEENModel(*args, **kwargs)

This is a wrapper class of pykeen.models.ERModel that allows to use the PyKEEN models in the mOWL framework.

RandomWalkPlusW2VModel(*args, **kwargs)

Embedding model that combines graph projections + random walks.

SyntacticPlusW2VModel(*args, **kwargs)

Model that combines corpus generation with Word2Vec training.

Class Inheritance Diagram

Inheritance diagram of mowl.models.elboxembeddings.model.ELBoxEmbeddings, mowl.models.elboxembeddings.examples.model_gda.ELBoxGDA, mowl.models.elboxembeddings.examples.model_ppi.ELBoxPPI, mowl.models.elembeddings.examples.model_gda.ELEmGDA, mowl.models.elembeddings.examples.model_ppi.ELEmPPI, mowl.models.elembeddings.model.ELEmbeddings, mowl.models.graph_kge.graph_pykeen_model.GraphPlusPyKEENModel, mowl.models.graph_random_walk.random_walk_w2v_model.RandomWalkPlusW2VModel, mowl.models.syntactic.w2v_model.SyntacticPlusW2VModel