jsPCA_robust: (numerically robust) Dimension reduction via Jensen-Shannon...
In text2vec: Modern Text Mining Framework for R
jsPCA_robust R Documentation
(numerically robust) Dimension reduction via Jensen-Shannon Divergence & Principal Components
Description
This function is largely a copy of the repsective function in
https://github.com/cpsievert/LDAvis/blob/master/R/createJSON.R, however,
with a fix to avoid log(0) proposed by Maren-Eckhoff in
https://github.com/cpsievert/LDAvis/issues/56
Usage
jsPCA_robust(phi)
Arguments
phi
matrix, with each row containing the distribution over terms
for a topic, with as many rows as there are topics in the model, and as
many columns as there are terms in the vocabulary.
text2vec documentation built on Nov. 9, 2023, 9:07 a.m.
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| jsPCA_robust | R Documentation |
(numerically robust) Dimension reduction via Jensen-Shannon Divergence & Principal Components
Description
This function is largely a copy of the repsective function in https://github.com/cpsievert/LDAvis/blob/master/R/createJSON.R, however, with a fix to avoid log(0) proposed by Maren-Eckhoff in https://github.com/cpsievert/LDAvis/issues/56
Usage
jsPCA_robust(phi)
Arguments
phi |
matrix, with each row containing the distribution over terms for a topic, with as many rows as there are topics in the model, and as many columns as there are terms in the vocabulary. |
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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