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Ángel Reyero Lobo

PROFILE

Ángel Reyero Lobo

Worked on enhancing the Permutation Feature Importance documentation for the lionelkusch/hidimstat repository, focusing on improving clarity, structure, and maintainability. Applied skills in documentation, machine learning, and statistical analysis to correct broken cross-references, clarify GLM coefficients, and update references related to Mean Decrease in Accuracy. Used reStructuredText to refine formatting, update headings, and improve overall readability, supporting faster onboarding and better user comprehension. The work emphasized careful attention to detail and collaborative editing, resulting in more accurate and navigable documentation. No code-level features or bug fixes were introduced, with all efforts concentrated on strengthening the project’s technical documentation.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

1Total
Bugs
0
Commits
1
Features
1
Lines of code
662
Activity Months1

Work History

January 2026

1 Commits • 1 Features

Jan 1, 2026

January 2026 monthly summary for the lionelkusch/hidimstat project. Focus was on improving Permutation Feature Importance (PFI) documentation. Deliverables centered on corrections and enhancements to existing content, enhancing accuracy, navigability, and maintainability of the PFI docs. No large-scale feature work or code changes reported this month beyond documentation improvements. The work demonstrates careful attention to detail, collaboration, and readiness for broader user adoption.

Activity

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Quality Metrics

Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

reStructuredText

Technical Skills

documentationmachine learningstatistical analysis

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

lionelkusch/hidimstat

Jan 2026 Jan 2026
1 Month active

Languages Used

reStructuredText

Technical Skills

documentationmachine learningstatistical analysis