Skip to main content

Rank based, multi-criteria aggregation method for explainable AI models.

Project description


Logo

A python package for a rank based, multi-criteria aggregation method for explainable AI models.

Repo Size Stars License Documentation Status


Read the Docs · Paper

About

Diagram

Explainability is crucial for improving the transparency of black-box machine learning models. With the advancement of explanation methods such as LIME and SHAP, various XAI performance metrics have been developed to evaluate the quality of explanations. However, different explainers can provide contrasting explanations for the same prediction, introducing trade-offs across conflicting quality metrics. Although available aggregation approaches improve robustness, reducing explanations’ variability, very limited research employed a multi-criteria decision-making approach. To address this gap, this package's paper introduces a multi-criteria rank-based weighted aggregation method that balances multiple quality metrics simultaneously to produce an ensemble of explanation models.

(back to top)

Installation

Run pip install xai-agg to install the package.

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

xai_agg-0.1.0.tar.gz (19.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

xai_agg-0.1.0-py3-none-any.whl (21.1 kB view details)

Uploaded Python 3

File details

Details for the file xai_agg-0.1.0.tar.gz.

File metadata

  • Download URL: xai_agg-0.1.0.tar.gz
  • Upload date:
  • Size: 19.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for xai_agg-0.1.0.tar.gz
Algorithm Hash digest
SHA256 2fb47b7ddf1736b00545d8491ef59f6c73f6e9180341b528f6458547ed76247a
MD5 47802800e6474dc80e0ffc356b121c8c
BLAKE2b-256 3ae9b6da52b298d4f8149c2070e6107ac10abeafb4f03cb5130360fefd0f0425

See more details on using hashes here.

Provenance

The following attestation bundles were made for xai_agg-0.1.0.tar.gz:

Publisher: python-publish.yml on hiaac-finance/xai_aggregation

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file xai_agg-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: xai_agg-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 21.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for xai_agg-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a9e362885fdef40650e09661464891a6a2e71d48c56c99c552e113b2966b9e09
MD5 3d2e05cdf55eae8da5cf94e4d2bffd86
BLAKE2b-256 84faf34aa5c5847b52394349affc0973040bab4117c3a42948cd89ae4d018f88

See more details on using hashes here.

Provenance

The following attestation bundles were made for xai_agg-0.1.0-py3-none-any.whl:

Publisher: python-publish.yml on hiaac-finance/xai_aggregation

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

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