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-0.1.208.tar.gz (30.2 kB view details)

Uploaded Source

File details

Details for the file ifra-0.1.208.tar.gz.

File metadata

  • Download URL: ifra-0.1.208.tar.gz
  • Upload date:
  • Size: 30.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10

File hashes

Hashes for ifra-0.1.208.tar.gz
Algorithm Hash digest
SHA256 d6c9600b92c8a400e27b13211919166d75c2705773ed4f42f3146411f2ae3214
MD5 971c4d6d746e0c20f3d7beef6d62723d
BLAKE2b-256 4fd7b687b8a9db5f47dfae9b59db6f65300fe57873dd5a069b35c195b037930b

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