EmbeddingMachine¶

class EmbeddingMachine(seed=42, dimensions=128, max_iter=20)[source]¶

Tool to compute Personalized PageRank based embeddings.

Methods Summary

`create_features`(target, feature_definition)	Calculate the edge features based on node embeddings.
`fit`(pagerank_scores)	Train an embedding model.

Methods Documentation

create_features(target, feature_definition)[source]¶

Calculate the edge features based on node embeddings.

Parameters

target (DataFrame) – A dataframe of drug-drug interactions.
feature_definition (Callable[[ndarray, ndarray], ndarray]) – A Tigerlily edge feature computation function.

Return type

ndarray

Returns

Drug pair features for each edge.

fit(pagerank_scores)[source]¶

Train an embedding model.

Parameters: pagerank_scores (DataFrame) – A dataframe of the top-k personalized PageRank scores.
Return type: DataFrame
Returns: A node embedding for each source.