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-2.3.1.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-2.3.1.tar.gz.
File metadata
- Download URL: fair_trees-2.3.1.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 |
a316ab05bf7865313d68cf7457c01b0c9caeb167790f13a421312a09a3a06a2a
|
|
| MD5 |
7c2f899edad50f83bf485fba26d2c8a5
|
|
| BLAKE2b-256 |
a66075f476d312edc626236d48e7fe042967e6a46f5cf5e6f7b368c9278ba991
|
File details
Details for the file fair_trees-2.3.1-py3-none-any.whl.
File metadata
- Download URL: fair_trees-2.3.1-py3-none-any.whl
- Upload date:
- Size: 7.0 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 |
247acf3741e1c44902d7c8d82e189b17c2c0085dce7bcbaa4263bc65b271daaf
|
|
| MD5 |
f28b3b073fea87611a5e619370d4227b
|
|
| BLAKE2b-256 |
06207dd4a908a4bc3c277d48c5f8b3acd0ad2a0a991ce554c9d389524b9fc2e8
|