Skip to main content

Reference implementation of LassoNet

Project description

PyPI version

LassoNet

This project is about performing feature selection in neural networks. At the moment, we support fully connected feed-forward neural networks. LassoNet is based on the work presented in this paper (bibtex here for citation). Here is a link to the promo video:

Promo Video

Code

We have designed the code to follow scikit-learn's standards to the extent possible (e.g. linear_model.Lasso).

To install it,

pip install lassonet

Our plan is to add more functionality that help users understand the important features in neural networks.

Website

LassoNet's website is https://lassonet.ml. It contains many useful references including the paper, live talks and additional documentation.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lassonet-0.0.2.tar.gz (8.5 kB view details)

Uploaded Source

Built Distribution

lassonet-0.0.2-py3-none-any.whl (9.3 kB view details)

Uploaded Python 3

File details

Details for the file lassonet-0.0.2.tar.gz.

File metadata

  • Download URL: lassonet-0.0.2.tar.gz
  • Upload date:
  • Size: 8.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

File hashes

Hashes for lassonet-0.0.2.tar.gz
Algorithm Hash digest
SHA256 d320a87fc8083d6953ebf49223fd67d6d14e47256c57dc68a92cb9afe30bdabc
MD5 e9523dc5b5f464269d7ff874d379541c
BLAKE2b-256 cf6f43ee1c8c63fca956c0e4879f48892eed10470cd4203f729879916923dc79

See more details on using hashes here.

File details

Details for the file lassonet-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: lassonet-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 9.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

File hashes

Hashes for lassonet-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 300b8791f9e3e3e0d4625e77f84cf0c2aa7e83e7f8b814264a6133a9a49d12c4
MD5 5c32dee3fc90f6a408efa6bb93808f8f
BLAKE2b-256 f7343923d08dfbf66ac0910d4309add9c19c452a81b2b4a276d932368fa1da6a

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page