word_topic_vector: Calculate Word-Topic Vector
In teramonagi/scdv: SCDV : Sparse Composite Document Vectors using soft clustering over distributional representations
Description
Calculate Word-Topic Vector
Usage
1
2
word_topic_vector(doc, k, dimension, word2vec_args = list(show_by = 25),
gmm_args = list())
Arguments
doc
List of document. each document
k
The number of clusters
dimension
The dimensions of word vector representations for every word
word2vec_args
Parameters for wrod2vec model ( parameters of wordVectors::train_word2vec )
gmm_args
Parameters for GMM model ( parameters of ClusterR::center_scale and ClusterR::GMM )
teramonagi/scdv documentation built on June 1, 2019, 3:58 a.m.
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Description
Calculate Word-Topic Vector
Usage
1 2 | word_topic_vector(doc, k, dimension, word2vec_args = list(show_by = 25),
gmm_args = list())
|
Arguments
doc |
List of document. each document |
k |
The number of clusters |
dimension |
The dimensions of word vector representations for every word |
word2vec_args |
Parameters for wrod2vec model ( parameters of wordVectors::train_word2vec ) |
gmm_args |
Parameters for GMM model ( parameters of ClusterR::center_scale and ClusterR::GMM ) |
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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