benchmark_causative: Benchmarking causative task
In beamandrew/cui2vec: cui2vec Word Embeddings for Multimodal Data

The benchmarking strategy leverages previously published ‘known’ relationships between medicalconcepts. We compare how similar the embeddings for a pair of concepts are by computing the cosine similarity of their corresponding vectors, and use this similarity to assess whether or not thetwo concepts are related. benchmark_causative assesses an embedding's ability to recover causes from the UMLS' table (MRREL) of entities known to be the cause of a certain result.

1 2	benchmark_causative(embedding_df, sig_level = 0.05, bootstraps = 10000, verbose = TRUE)

`embedding_df`	The embedding data frame with bound semantic type
`sig_level`	The significance level threshold
`bootstraps`	The number of boostraps to perform
`verbose`	Flag for verbosity