Pypgx MLlib¶
Graph machine learning tools for use with PGX.
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class
pypgx.api.mllib.
DeepWalkModel
(java_deepwalk_model)¶ Bases:
pypgx.api._pgx_context_manager.PgxContextManager
DeepWalk model object.
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compute_similars
(v, k)¶ Compute the top-k similar vertices for a given vertex.
- Parameters
v – id of the vertex or list of vetex ids for which to compute the similar vertices
k – number of similars to return
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destroy
()¶ Destroy this model object.
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export
()¶ Return a ModelStore object which can be used to save the model.
- Returns
ModelStore object
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fit
(graph)¶ Fit the model on a graph.
- Parameters
graph – Graph to fit on
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store
(path, key, overwrite=False)¶ Store the model in a file.
- Parameters
path – Path where to store the model
key – Encryption key
overwrite – Whether or not to overwrite pre-existing file
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property
trained_vectors
¶ Get the trained vertex vectors for the current DeepWalk model.
- Returns
PgxFrame object with the trained vertex vectors
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class
pypgx.api.mllib.
GraphWiseConvLayerConfig
(java_config, params)¶ Bases:
object
GraphWise conv layer configuration.
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class
pypgx.api.mllib.
GraphWiseDgiLayerConfig
(java_config, params)¶ Bases:
object
GraphWise dgi layer configuration.
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class
pypgx.api.mllib.
GraphWisePredictionLayerConfig
(java_config, params)¶ Bases:
object
GraphWise prediction layer configuration.
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class
pypgx.api.mllib.
Pg2vecModel
(java_pg2vec_model)¶ Bases:
pypgx.api._pgx_context_manager.PgxContextManager
Pg2Vec model object.
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compute_similars
(graphlet_id, k)¶ Compute the top-k similar graphlets for a list of input graphlets.
- Parameters
graphlet_id – graphletIds or iterable of graphletIds
k – number of similars to return
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destroy
()¶ Destroy this model object.
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export
()¶ Return a ModelStore object which can be used to save the model.
- Returns
ModelStore object
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fit
(graph)¶ Fit the model on a graph.
- Parameters
graph – Graph to fit on
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infer_graphlet_vector
(graph)¶ - Parameters
graph – graphlet for which to infer a vector
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infer_graphlet_vector_batched
(graph)¶ - Parameters
graph – graphlets (as a single graph but different graphlet-id) for which to infer vectors
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store
(path, key, overwrite=False)¶ Store the model in a file.
- Parameters
path – Path where to store the model
key – Encryption key
overwrite – Whether or not to overwrite pre-existing file
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property
trained_graphlet_vectors
¶ Get the trained graphlet vectors for the current pg2vec model.
- Returns
PgxFrame containing the trained graphlet vectors
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class
pypgx.api.mllib.
SupervisedGraphWiseModel
(java_graphwise_model, params={})¶ Bases:
pypgx.api.mllib._graphwise_model.GraphWiseModel
SupervisedGraphWise model object.
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export
()¶ Return a ModelStore object which can be used to save the model.
- Returns
ModelStore object
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fit
(graph)¶ Fit the model on a graph.
- Parameters
graph – Graph to fit on
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store
(path, key, overwrite=False)¶ Store the model in a file.
- Parameters
path – Path where to store the model
key – Encryption key
overwrite – Whether or not to overwrite pre-existing file
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class
pypgx.api.mllib.
UnsupervisedGraphWiseModel
(java_graphwise_model, params={})¶ Bases:
pypgx.api.mllib._graphwise_model.GraphWiseModel
UnsupervisedGraphWise model object.
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export
()¶ Return a ModelStore object which can be used to save the model.
- Returns
ModelStore object
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fit
(graph)¶ Fit the model on a graph.
- Parameters
graph – Graph to fit on
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store
(path, key, overwrite=False)¶ Store the model in a file.
- Parameters
path – Path where to store the model
key – Encryption key
overwrite – Whether or not to overwrite pre-existing file
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