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AI-Driven Anomaly Detection for Data Quality

0packages depend
4Kdownloads / year
27.9%test coverage
13/13checks pass

Overview

About
Maintained by Vikrant Dev RathoreFirst published 2026-01-151 releasesCRAN page ↗GitHub ↗

Automated data quality auditing using unsupervised machine learning. Provides AI-driven anomaly detection for data quality assessment, primarily designed for Electronic Health Records (EHR) data, with benchmarking capabilities for validation and publication. Methods based on: Liu et al. (2008) doi:10.1109/ICDM.2008.17, Breunig et al. (2000) doi:10.1145/342009.335388.

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Health

CRAN checks
13OK
Slowest check: 2.5 min · r-devel-linux-x86_64-fedora-clang
Check history
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

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4K
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Rank #7,602 · ~11/day · ~335/mo
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Repository

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Last activity 2026-01-10

Repository practices

Upstream repositoryBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/vikrant31/autoflagr on 2026-07-19.

Continuous integration (1)
GitHub Actions
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
13 external dependencies (excludes base and recommended)
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Code & Tests

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Maintainer (1)
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Authors (1)
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Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.0Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2026-01-15
Total releases
1 / 1 yrs
License
MIT + file LICENSE OSI
Download size
761 KB
Installed size
not tracked yet
With dependencies
not tracked yet
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