Comments (2)
Word2vec learns two matrices--call them an embedding and a context vector (although this might not be appropriate for every method). The embedding matrix is the "model" that's returned by this package; it can be extracted by model <- train_word2vec(...)
or read.vectors(...)
. The context vector is (I think) just thrown away after training, which is too bad because it can be useful in some situations.
Curious if you really want both or just the embedding matrix. I'd be willing to leave an issue open for the context vectors if there's a use for them.
from wordvectors.
I'd certainly be interested in recovering the context vectors as well, if this is feasible. This package is pretty awesome, btw.
from wordvectors.
Related Issues (20)
- how convert a data frame or table to a VectorSpaceModel?
- Fatal Error on 1 MB file HOT 2
- is wordVectors on cran? HOT 2
- plot function not working HOT 1
- How to get plot points HOT 1
- problem to call library
- float?
- n-grams greater than 2 HOT 1
- could not find the cookbook data
- is there a way to get the token frequencies
- examples of reject
- This package is not available for 3.5. HOT 2
- rword2vec, R session aborted HOT 1
- Working with date-time format, cant handle POSIXct. (Error in as.POSIXlt.numeric(x) : 'origin' must be supplied)
- include vignette?
- Error in train_word2vec: "Error in if (binary) { : argument is of length zero" HOT 1
- Unable to compile with gcc 10 | Arch Linux solution = downgrade HOT 2
- Does it accept Arabic (or any non-ASCII) in general?
- Chinese is not available HOT 3
- Using formulas in `closest_to()` may result in an error (R 4.2.0) HOT 4
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from wordvectors.