Description Usage Arguments Value
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_semantic_type
assesses an ability to identify semantic types. Semantic types are
meta-information about which category a concept belongs to, and these categories are arranged in a hierarchy.
1 2 | benchmark_semantic_type(embedding_df, sig_level = 0.05,
bootstraps = 10000)
|
embedding_df |
The embedding dataframe with bound semantic types |
sig_level |
The significance level threshold |
bootstraps |
The number of bootstraps to perform |
Dataframe of performance on this task per semantic type
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