This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.
Project description
The author of this package has not provided a project description
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
fair_trees-2.1.tar.gz
(6.8 kB
view details)
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 fair_trees-2.1.tar.gz.
File metadata
- Download URL: fair_trees-2.1.tar.gz
- Upload date:
- Size: 6.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.11.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d7ee2c326dde0fdcdc1d822b7bb4f0a3600b7170b414d6bf872bd39cd90eb20d
|
|
| MD5 |
2a6fbb703acd543db54deb90fb0c66d3
|
|
| BLAKE2b-256 |
6529bab1ad7e302ec563b3a0fdd1f77414206a3e79acd4104f3956d0e556c188
|
File details
Details for the file fair_trees-2.1-py3-none-any.whl.
File metadata
- Download URL: fair_trees-2.1-py3-none-any.whl
- Upload date:
- Size: 6.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.11.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
7ef966273effd00cd11c4549ca7e5a176ead18eb7d40f3b1c07050789419eeb9
|
|
| MD5 |
2e90468627de3aea92a16ca6828948a7
|
|
| BLAKE2b-256 |
3e4395cc0427fce3703fe5a82c84c160ca42e7848a98a7da6d678c84fa595e74
|