benchmark_similarity: Benchmarking similarity task
In beamandrew/cui2vec: cui2vec Word Embeddings for Multimodal Data
Description
Usage
Arguments
Value
Description
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.
link{benchmark_similarity} reports the spearman correlation between the human assessment scores
and cosine similarity from the embeddings.
Usage
1
benchmark_similarity(embedding_df)
Arguments
embedding_df
The embedding dataframe
Value
Dataframe of relatedness
beamandrew/cui2vec documentation built on Nov. 4, 2019, 7:07 a.m.
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Description Usage Arguments Value
Description
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.
link{benchmark_similarity} reports the spearman correlation between the human assessment scores
and cosine similarity from the embeddings.
Usage
1 | benchmark_similarity(embedding_df)
|
Arguments
embedding_df |
The embedding dataframe |
Value
Dataframe of relatedness
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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