-
Notifications
You must be signed in to change notification settings - Fork 0
Let's find out 25 most common topics (their keywords) from 20000 texts using LDA topic modelling. We will test whether filtering of the corpus by tf-idf will improve accuracy of topic estimation. For more details please refer to the ipython notebook.
springlaughing/Topic-modelling-with-LDA-on-Russian-Texts
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
About
Let's find out 25 most common topics (their keywords) from 20000 texts using LDA topic modelling. We will test whether filtering of the corpus by tf-idf will improve accuracy of topic estimation. For more details please refer to the ipython notebook.
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published