topicvec

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LogLikelihood

2

Hi askerlee! I would ask you if the logLikelihood computed by "calcLoglikelihood" function is normalised by the number of words in the corpus? If not, it could be easily done?...

gabrer

Sentences within a dataset

2

I am working on a dataset quite "noisy", so it's very difficult to exactly detect a sentence (for example, I have a lot of abbreviation with points, so these points...

gabrer

Training on dataset without categories

3

Hi! I have a corpus of documents without categories, and I would generate topics without adding this kind of information. However, it seems that this code is only oriented to...

gabrer

if i want to try it on other language, how to train 25000-180000-500-BLK-8.0.vec.npy? and..

6

hi all, if i want to try it on other language, how can i train 25000-180000-500-BLK-8.0.vec.npy and get top1grams-wiki.txt? for example chinese language, I have pre trained w2v model of...

zzks

Problem about input embeddings generated by other algo.

5

Hi, I noticed that in your paper 6.1, as the inefficiency of optimizing likelihood function including both **Z** and **V**, you choose to divide the process into two stages. First,...

geekinglcq