model_norm: Normalization Model
In news-r/gensimr: Topic Modelling
Description
Usage
Arguments
Details
Examples
Description
Compute the l1 or l2 normalization by normalizing separately for each document in a corpus.
Usage
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Arguments
corpus
Model as returned by wrap.
norm
Norm used to normalize, defaults to l2.
file
Path to a saved model.
Details
Target dimensionality (num_topics) of 200–500 is recommended as a “golden standard” https://dl.acm.org/citation.cfm?id=1458105.
Examples
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docs <- prepare_documents(corpus)
dictionary <- corpora_dictionary(docs)
corpora <- doc2bow(dictionary, docs)
# fit model
norm <- model_norm(corpora)
news-r/gensimr documentation built on Jan. 9, 2021, 5:55 a.m.
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Description Usage Arguments Details Examples
Description
Compute the l1 or l2 normalization by normalizing separately for each document in a corpus.
Usage
1 2 3 |
Arguments
corpus |
Model as returned by |
norm |
Norm used to normalize, defaults to |
file |
Path to a saved model. |
Details
Target dimensionality (num_topics) of 200–500 is recommended as a “golden standard” https://dl.acm.org/citation.cfm?id=1458105.
Examples
1 2 3 4 5 6 | docs <- prepare_documents(corpus)
dictionary <- corpora_dictionary(docs)
corpora <- doc2bow(dictionary, docs)
# fit model
norm <- model_norm(corpora)
|
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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