Class frequency estimation
Project description
freq-e = (class) frequency estimation
Frequency estimation of classes. This is also known as prevalence estimation (in statatistics and epidemiology), quantification (in data mining), and class prior estimation (in machine learning).
This is software to accompany the paper "Uncertainty-aware generative models for inferring document class prevalence" by Katherine Keith and Brendan O'Connor published in EMNLP 2018. Companion paper url here: http://aclweb.org/anthology/D18-1487
Contact
Contact the software authors with any questions: Katherine Keith (kkeith@cs.umass.edu) and Brendan O'Connor (brenocon@cs.umass.edu).
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
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file freq-e-0.1.0.tar.gz.
File metadata
- Download URL: freq-e-0.1.0.tar.gz
- Upload date:
- Size: 8.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.4.2 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.28.1 CPython/3.7.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
067a7303fd8f3cfcfd162e487d954ca96e0552464cea404402efddd4a8afbf4b
|
|
| MD5 |
aaef355f7d9b99b1450f2f518bb10af5
|
|
| BLAKE2b-256 |
9002c3a7932e787c16352688f432ff7547318d0c786530c209cf736cf4cc34d0
|
File details
Details for the file freq_e-0.1.0-py3-none-any.whl.
File metadata
- Download URL: freq_e-0.1.0-py3-none-any.whl
- Upload date:
- Size: 10.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.4.2 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.28.1 CPython/3.7.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
45fd0047cf2edf59873306066da50e37b28370863b66e2c18f3a1e486675c4eb
|
|
| MD5 |
3c8cf3ac04f7687a450935dabb80a051
|
|
| BLAKE2b-256 |
35f2f754529e6e0fdec2989e4e2afcf14b580d81aa7b3b7381c5823a3a271f6a
|
