A topic models algorithm
Project description
Welcome
ProSiT - PROgressive SImilarity Thresholds is an algorithm for topic models.
Documentation at readthedocs.
You can try ProSiT on this colab notebook.
For technical details and citation, please refer to:
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
prosit-0.1.5.tar.gz
(11.6 kB
view details)
Built Distribution
prosit-0.1.5-py3-none-any.whl
(10.9 kB
view details)
File details
Details for the file prosit-0.1.5.tar.gz
.
File metadata
- Download URL: prosit-0.1.5.tar.gz
- Upload date:
- Size: 11.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.10.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5204cbe219719783ac4ca828e5e0daa0c1f2d9baaa7e1d3f4473317f9ea2b69e |
|
MD5 | 25c2c519398fdc84d42a97f308c9844f |
|
BLAKE2b-256 | 2bcb534f4dc812d91d74fedd8403cbfc86931a2a8c30c08897cfdce8ef6689d7 |
File details
Details for the file prosit-0.1.5-py3-none-any.whl
.
File metadata
- Download URL: prosit-0.1.5-py3-none-any.whl
- Upload date:
- Size: 10.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.10.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | ae35ff4ace1a5191a330a98c61b682be4b9c0164fc34e0ae4336458814d94cb7 |
|
MD5 | c1ad16877dff58acefd6e739460abf8a |
|
BLAKE2b-256 | 43db007afd113c0a742268491e8ce619e9879fa79b284b9f4de73fb9def645a5 |