[R] progress of LDA algorithm...

Bert Gunter bgunter@4567 @end|ng |rom gm@||@com
Sat Jan 29 21:34:47 CET 2022


I presume this is in some specialized package that you have not told
us about -- topicmodels maybe? It is therefore off topic here. In any
case, this is the sort of question for which you should contact the
package maintainer (?maintainer).

As your question may also intersect with high performance computing
considerations, you might want to post  it on the R-Sig-HPC list,
https://stat.ethz.ch/mailman/listinfo/r-sig-hpc

Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

On Sat, Jan 29, 2022 at 8:27 AM akshay kulkarni <akshay_e4 using hotmail.com> wrote:
>
> dear members,
>                           I want to run LDA(latent Dirichlet allocation) on certain news articles. i have the following questions:
>
>
>   1.  Is there any way to know the progress of the execution of the LDA algorithm?
>   2.  I read in SO that if you have more memory, faster is the execution time of LDA. I am using AWS z1d instance with 48 cores and about 325 GB RAM. I have multiple categories of news, but one of them is much larger than others, containing about 25000 articles. Is it preferable to send those categories individually to different processors, and whether R frees up the memory after running on the smaller categories so that the largest category can run with more memory? Or is it preferable to first run the smaller sets, finish the job, and then run the largest category?
>
> Thanking You,
> Yours sincerely,
> AKSHAY M KULKARNI
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.



More information about the R-help mailing list