Run dynamic topic modeling
Project description
#hide
dynamic_topic_modeling
Run dynamic topic modeling.
The goal of wei_lda_debate
is to build Latent Dirichlet Allocation
models based on sklearn
and gensim
framework, and Dynamic Topic
Model(Blei and Lafferty 2006) based on gensim
framework. I decide to
build a Python package, so this reposority will be updated. The new
reposority path is
https://github.com/JiaxiangBU/dynamic_topic_modeling.git.
Install
pip install dynamic_topic_modeling
How to use
Code of Conduct
Please note that the dynamic_topic_modeling
project is released with a
Contributor Code of
Conduct.
By
contributing to this project, you agree to abide by its terms.
License
Apache License 漏 Jiaxiang Li and Shuyi Wang
Blei, David M., and John D. Lafferty. 2006. "Dynamic Topic Models." In Machine Learning, Proceedings of the Twenty-Third International Conference (Icml 2006), Pittsburgh, Pennsylvania, Usa, June 25-29, 2006.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for dynamic_topic_modeling-1.0.1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 488016c74657af285e28c5b8ffa269eed06bc399e54f7dcff265e91beafa99bb |
|
MD5 | 7c54685764c1cc1516fa0fccaca7b1dc |
|
BLAKE2b-256 | 7ece22c927b7e29812116e152713e741846e8db70c4530fa93218837770eef5a |
Hashes for dynamic_topic_modeling-1.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 94afd09cb598e353171bdf94986f885f4774609eb62090f9492a39bc14879360 |
|
MD5 | 8ec7812f773db4e265ac1010aae80989 |
|
BLAKE2b-256 | 42dcdf95fba51aebe7c69e2724da18ce20b2825b94d63388c604abbcb2edf217 |