Skip to main content

Interpretable Federated Rule Algorithm

Project description


permalink: /docs/index.html

The complete documentation is available at https://advestis.github.io/ifra/

Interpretable Federated Rule Algorithm

This algorithm generates an interpretable explaining ruleset based on a target Y and features X through a federated learning, where each node generates a ruleset from a single decision tree.

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

ifra-0.1.160.tar.gz (27.6 kB view details)

Uploaded Source

File details

Details for the file ifra-0.1.160.tar.gz.

File metadata

  • Download URL: ifra-0.1.160.tar.gz
  • Upload date:
  • Size: 27.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.10

File hashes

Hashes for ifra-0.1.160.tar.gz
Algorithm Hash digest
SHA256 9b042bdb6a9ae3492b388a54f65a941071c944d9246174e5d8c88ff5b49189d0
MD5 d8210b910507b780963451054ef8bf14
BLAKE2b-256 31eb0c45177284e292ec19f87d84cef232ff7ac0318950464d9816af28ad653b

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