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-0.1.80.tar.gz (22.8 kB view details)

Uploaded Source

File details

Details for the file ifra-0.1.80.tar.gz.

File metadata

  • Download URL: ifra-0.1.80.tar.gz
  • Upload date:
  • Size: 22.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for ifra-0.1.80.tar.gz
Algorithm Hash digest
SHA256 ada2648d52a2c9e972ed0f13f307fd43c236dd25a670f789d4c3d92e98fc1b9e
MD5 ddc0e724de05eb43c00b05ff87f54cc4
BLAKE2b-256 2a1a01a4f83647378262dc7fc96a81dfbad482a91ece1aa48dd7cef2cfb94cf8

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