dhis2-chap/chap-core
Jan 2026 – Jan 2026
1 Month active
Languages Used
MarkdownPython
Technical Skills
API developmentPythonPython programmingdata analysisdata modelingdata science
audun
PROFILE
Audun
Audun developed and integrated the ExtendedPredictor class for the dhis2-chap/chap-core repository, enabling iterative predictions beyond a model’s maximum prediction length and supporting dynamic evaluation lengths. Using Python and data modeling, Audun embedded this feature into existing evaluation workflows, ensuring compatibility with evaluate, evaluate2, and evaluate_hpo processes. The work included comprehensive documentation and tutorials to facilitate adoption. Audun also addressed a bug affecting cross-iteration prediction accuracy and historic data updates, improving the reliability of multi-step forecasting. The project demonstrated depth in API development, machine learning, and unit testing, resulting in more robust and flexible evaluation capabilities for the codebase.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
4Total
Bugs
1
Commits
4
Features
1
Lines of code
1,330
Activity Months1
Your Network
26 peopleShared Repositories
26
Abyot Asalefew GizawMember
Andreas JensenMember
Andre gregussenMember
AndreGreguMember
BumpVersion ActionMember
kanduricMember
Eirik HaugstulenMember
geirksaMember
HalvardgithubMember
Work History
January 2026
4 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary focused on delivering flexible evaluation capabilities, stabilizing iterative predictions, and improving data integrity. Key enhancements include introducing an ExtendedPredictor wrapper for iterative predictions beyond a model's maximum length, integrating it into the evaluation workflow, and expanding developer resources with documentation and tutorials. A targeted bug fix addresses cross-iteration prediction accuracy and historic data updates to ensure robust and reliable multi-step forecasting.
4 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary focused on delivering flexible evaluation capabilities, stabilizing iterative predictions, and improving data integrity. Key enhancements include introducing an ExtendedPredictor wrapper for iterative predictions beyond a model's maximum length, integrating it into the evaluation workflow, and expanding developer resources with documentation and tutorials. A targeted bug fix addresses cross-iteration prediction accuracy and historic data updates to ensure robust and reliable multi-step forecasting.
January 2026
Activity
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Quality Metrics
Correctness90.0%
Maintainability85.0%
Architecture90.0%
Performance85.0%
AI Usage25.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
API developmentPythonPython programmingdata analysisdata modelingdata sciencedocumentationfeature developmentmachine learningmodel evaluationsoftware developmentunit testing
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