Hibachi
Hibachi is a Python package that implements feature selection methods for PyTorch.
Installation
Run the following command:
pip install hibachi
References
@incollection {
NIPS2017_7270,
title = {Kernel Feature Selection via Conditional Covariance Minimization},
author = {Chen, Jianbo and Stern, Mitchell and Wainwright, Martin J and
Jordan, Michael I},
booktitle = {Advances in Neural Information Processing Systems 30},
editor = {I. Guyon and U. V. Luxburg and S. Bengio and H. Wallach and R.
Fergus and S. Vishwanathan and R. Garnett},
pages = {6949--6958},
year = {2017},
publisher = {Curran Associates, Inc.},
url = {http://papers.nips.cc/paper/7270-kernel-feature-selection-via-conditional-covariance-minimization.pdf}
}
1 maintainer
Metadata
1 maintainer
Release files for hibachi 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| hibachi-0.0.1.tar.gz | 4.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hibachi-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.0 kB
Release files / hibachi-0.0.1.tar.gz
| Download URL | hibachi-0.0.1.tar.gz |
|---|---|
| Size | 4.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
4a44f129a275c5f51e2769febf29ab8af0670adbb07cebc9e4ec3bf01aa033fb
|
|
BLAKE2b-256 checksum How to use checksums |
3157c052676fabaed0b392caa893ac94b147f1c1d1710d88bf498fb2512d3479
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.6.5
|
Release files / hibachi-0.0.1-py3-none-any.whl
| Download URL | hibachi-0.0.1-py3-none-any.whl |
|---|---|
| Size | 13.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
f2057516afbc26571b91e6336804e87e41ec2546bdcc2519c8b885c8344cc55e
|
|
BLAKE2b-256 checksum How to use checksums |
b1bfa585ac5dd61f7b8638b26360b32b6259a818f0b35c39155a5be81db914dd
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.6.5
|
Security for hibachi 0.0.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
