pyFOCI - Feature Ordering by Conditional Independence
pyFOCI provides the feature selection algorithm "Feature Ordering by Conditional Independence" (FOCI), based on a nonlinear generalization of the partial R² statistic. So it can be especially useful in strongly nonlinear data scenarios.
It is based on
-
Mona Azadkia and Sourav Chatterjee. A simple measure of conditional dependence. The Annals of Statistics, 49(6):3070–3102, 2021. [DOI] [arXiv]
-
Sebastian Fuchs. Quantifying directed dependence via dimension reduction. Journal of Multivariate Analysis 201 (2024): 105266. [DOI] [arXiv]
The Package is scikit-learn compatible. It is available on PyPI.
Refer to the documentation (API and example code) at https://m3dm-jku.github.io/pyFOCI/ .
This work has been supported by the COMET-K2 Center of the Linz Center of Mechatronics (LCM), funded by the Austrian federal government and the federal state of Upper Austria.
1 maintainer
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 pyfoci-0.6.0.tar.gz.
File metadata
- Download URL: pyfoci-0.6.0.tar.gz
- Upload date:
- Size: 165.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via:
twine/7.0.0 CPython/3.13.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f6aa2e4df09bff8aeddafc4857701d20c6e19bcc35e2a829d9ecdf552f560189
|
|
| MD5 |
e2234c3faba488135b44e10c73d347f0
|
|
| BLAKE2b-256 |
11cf0016694b9f7eda20c8ca7141c218e617f2aa78980ac00fff58922a7a3e86
|
Provenance
The following attestation bundles were made for pyfoci-0.6.0.tar.gz:
Publisher:
release.yml on m3dm-jku/pyFOCI
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
pyfoci-0.6.0.tar.gz -
Subject digest:
f6aa2e4df09bff8aeddafc4857701d20c6e19bcc35e2a829d9ecdf552f560189 - Sigstore transparency entry: 2300334455
- Sigstore integration time:
-
Permalink:
m3dm-jku/pyFOCI@900f1d73a91b52033df0ac98dc7aee453dfd9ce4 -
Branch / Tag:
refs/tags/v0.6.0 - Owner: https://github.com/m3dm-jku
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
release.yml@900f1d73a91b52033df0ac98dc7aee453dfd9ce4 -
Trigger Event:
push
-
Statement type:
File details
Details for the file pyfoci-0.6.0-py3-none-any.whl.
File metadata
- Download URL: pyfoci-0.6.0-py3-none-any.whl
- Upload date:
- Size: 21.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via:
twine/7.0.0 CPython/3.13.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b9593c40c49c9952d2d7747c176bd0448a98d9a98714138c088e04f3c7a9be57
|
|
| MD5 |
97e82247960a7021a2a8ae480696243f
|
|
| BLAKE2b-256 |
5190ab344b6ee68169af6e9caae27c25aabc5f054941de923e602fbd2fbb8422
|
Provenance
The following attestation bundles were made for pyfoci-0.6.0-py3-none-any.whl:
Publisher:
release.yml on m3dm-jku/pyFOCI
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
pyfoci-0.6.0-py3-none-any.whl -
Subject digest:
b9593c40c49c9952d2d7747c176bd0448a98d9a98714138c088e04f3c7a9be57 - Sigstore transparency entry: 2300334485
- Sigstore integration time:
-
Permalink:
m3dm-jku/pyFOCI@900f1d73a91b52033df0ac98dc7aee453dfd9ce4 -
Branch / Tag:
refs/tags/v0.6.0 - Owner: https://github.com/m3dm-jku
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
release.yml@900f1d73a91b52033df0ac98dc7aee453dfd9ce4 -
Trigger Event:
push
-
Statement type:
