Ethos AI Guardian: Automated bias detection and mitigation for machine learning models.
Project description
Ethos AI Guardian
Ethos AI Guardian is a powerful, automated bias detection and mitigation toolkit for machine learning models. Built specifically for data scientists, it provides a seamless pipeline to identify historical, confounding, and selection biases in your datasets, and mitigates them using state-of-the-art techniques.
Features
- Automated Bias Detection: Quickly scan datasets for Statistical Parity, Disparate Impact, and Equal Opportunity differences.
- Deep Contextual Debiasing: Pro-level Tabular Transformers to understand contextual bias in categorical and numerical features.
- Adversarial Mitigation: Uses an adversarial debiasing architecture to enforce fairness without sacrificing predictive power.
- Pipelines: Easy-to-use Scikit-Learn style pipelines for integrating into your existing workflow.
Installation
You can install ethos_ai_guardian using pip:
pip install ethos_ai_guardian
Quick Start
import pandas as pd
from ethos_ai_guardian import AntiBiasPipeline
# Load your dataset
df = pd.read_csv("your_data.csv")
# Initialize the pipeline
pipeline = AntiBiasPipeline(model_type='logistic')
# Run automated bias mitigation
results = pipeline.train_and_evaluate(
df=df,
features=['age', 'income', 'education'],
sensitive_attr='gender',
target_col='approved'
)
print(results["fairness_metrics"])
License
MIT License
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