trustlens 0.3.0

Analyze machine learning model reliability beyond accuracy.

Your model has 92% accuracy. That may still be unsafe.

TrustLens is an open-source Python library for evaluating model reliability beyond accuracy and producing deployment-ready decisions.

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Why TrustLens

Most model evaluations stop at accuracy, AUC, or F1. Deployment decisions require more:

• Can we trust model probabilities?
• Are failures concentrated in high-confidence regions?
• Is performance uneven across sensitive groups?
• Are we shipping a model with hidden reliability risk?

TrustLens answers these questions in one pipeline and produces:

• module-level diagnostics (calibration, failure, bias, representation)
• a composite Trust Score (0-100)
• penalty and blocker reasoning
• a deployment verdict suitable for review and CI gating

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Quickstart

Install

pip install trustlens

Analyze a Model

from trustlens import analyze

report = analyze(model, X_test, y_test, y_prob=model.predict_proba(X_test))
report.show()

Example Output

TRUST SCORE: 88/100 [B]
Assessment : Good Trust - minor issues to address

Score Summary:
  Base Score        : 92
  Penalties Applied : -4.0 [Calibration (-4.0)]
  Final Score       : 88

Compare Candidates

from trustlens import compare

compare([report_model_a, report_model_b, report_model_c])

Export Artifacts

report.save("report.json")   # machine-readable
report.save("report.txt")    # human-readable
report.save("trust_report")  # full bundle with plots + metadata

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One-Line Demo

from trustlens import quick_analyze
quick_analyze(dataset="breast_cancer")

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Contributors

Khanz9664

jayssSmm

WeiGuang-2099

CrepuscularIRIS

komoike-oss28-ui

sidharth-vijayan

MustansirNisar

Want to see your name here? Start with a good first issue.

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Citation

If you use TrustLens in research or production, cite:

@software{trustlens2026,
  author = {Shahid Ul Islam},
  title  = {TrustLens: Debug your ML models beyond accuracy},
  year   = {2026},
  url    = {https://github.com/Khanz9664/TrustLens},
}

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Author

Shahid Ul Islam GitHub · Portfolio · LinkedIn