scikit-learn-contrib/MAPIE
Dec 2025 – Dec 2025
1 Month active
Languages Used
Python
Technical Skills
Pythondata sciencemachine learningscikit-learnstatistical modeling
OmG
PROFILE
Omg
Omid Gheibi developed a major calibration feature for the scikit-learn-contrib/MAPIE repository, focusing on improving probabilistic estimates in both binary and multi-class classification tasks. He implemented the Venn-Abers calibration method using Python and scikit-learn, enabling models to produce more reliable probability outputs for downstream applications such as risk scoring and reliability analysis. Omid ensured the robustness of this feature by adding comprehensive docstrings, tests, and coverage, as well as practical usage examples in the documentation. His work demonstrated depth in statistical modeling and machine learning, addressing the need for well-calibrated probabilities in real-world decision-making scenarios.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
2,650
Activity Months1
Your Network
17 peopleShared Repositories
17
Work History
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 Monthly Summary: Implemented a major calibration feature in MAPIE to improve probabilistic estimates for both binary and multi-class classification, accompanied by documentation, tests, and practical usage examples. This work enhances model trust and decision-making for downstream tasks relying on calibrated probabilities, such as risk scoring and reliability analyses.
1 Commits • 1 Features
Dec 1, 2025December 2025 Monthly Summary: Implemented a major calibration feature in MAPIE to improve probabilistic estimates for both binary and multi-class classification, accompanied by documentation, tests, and practical usage examples. This work enhances model trust and decision-making for downstream tasks relying on calibrated probabilities, such as risk scoring and reliability analyses.
December 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture100.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Pythondata sciencemachine learningscikit-learnstatistical modeling
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