as.textmodel_lss {LSX} | R Documentation |
Create a Latent Semantic Scaling model from various objects
Description
Create a new textmodel_lss object from an existing or foreign objects.
Usage
as.textmodel_lss(x, ...)
Arguments
x |
an object from which a new textmodel_lss object is created. See details. |
... |
arguments used to create a new object. |
Details
If x
is a textmodel_lss, original word vectors are reused to compute polarity
scores with new seed words. It is also possible to subset word vectors via slice
if it was trained originally using SVD.
If x
is a dense matrix, it is treated as a column-oriented word vectors with which
polarity of words are computed. If x
is a named numeric vector, the values are treated
as polarity scores of the words in the names.
If x
is a normalized wordvector::textmodel_word2vec, it returns a spatial model;
if not normalized, a probabilistic model. While the polarity scores of words are
their cosine similarity to seed words in spatial models, they are
predicted probability that the seed words to occur in their proximity.
Value
a dummy textmodel_lss object