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autoFlagR

1.0.0Package record

AI-Driven Anomaly Detection for Data Quality

0packages depend
5Kdownloads / year
27.9%test coverage
13/13flavors OK

Overview

About

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.

Changes in 1.0.0

Version 1.0.0 (2025-12-22)

Core Functionality

  • prep_for_anomaly(): Automated data preprocessing for anomaly detection
  • score_anomaly(): Anomaly scoring using Isolation Forest and Local Outlier Factor
  • flag_top_anomalies(): Flagging records as anomalous based on threshold or contamination rate
  • generate_audit_report(): Generate comprehensive PDF, HTML, and DOCX audit reports

Benchmarking

  • extract_benchmark_metrics(): Extract performance metrics (AUC-ROC, AUC-PR, Top-K Recall)
  • calculate_benchmark_metrics(): Calculate metrics from scored data with ground truth

Utilities

  • get_top_anomalies(): Retrieve top N most anomalous records
  • Feature importance calculation for explaining anomalies
Show all changes in 1.0.0Hide the rest of the changes in 1.0.0

Features

  • Support for multiple anomaly detection algorithms (Isolation Forest, LOF)
  • Automated preprocessing (ID handling, scaling, encoding)
  • Professional report generation with visualizations
  • Benchmarking capabilities for validation studies
  • Tidyverse-compatible interface

Documentation

  • Comprehensive function documentation
  • Getting started vignette
  • Healthcare example vignette
  • Benchmarking tutorial

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 2.3 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-09-08
  • ERROR12 OK, 1 ERROR2026-09-07
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
Show 2 earlier changesHide 2 earlier changes
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.0.0
README· In the repository, left out of the releaseVignettesYes · 3 · dynamicNEWSYes · 100% structured · mentions 1.0.0Citation fileYes · software entry onlyWebsiteYes · pkgdown
Help pages
11 (2 internal)
Examples that run
14%1 run in a plain check · 6 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
78%
Documented parameters
not tracked
Return-value docs
not tracked
Help pages citing references
0%

Downloads

5K
CRAN downloads in the past year
Rank #10,102 · ~14/day · ~418/mo
Daily download trend is not available in this view yet.
33030 days
99390 days
5K1 year
Compare downloads with other packages →
Also on66 r2u21 autocran

Repository

0Stars
0Forks
0Open issues
0Open PRs
0Releases
Last activity 2026-01-10
Responsiveness
not measured
PracticesBeta

4 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/vikrant31/autoflagr on 2026-10-18.

Continuous integration (1)
GitHub Actions
Docs source (3)
pkgdown

GitHub Pages site last deployed 2026-01-10 · The repository has a site deploy workflow

pkgdown site last built 2026-01-10, before release 1.0.0 (2026-01-15)

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
13 external dependencies (excludes base and recommended)

Installing autoFlagR adds 65 packages (34 with compiled code, 50 MB of source tarballs). Heaviest: ggplot2 6.0 MB, bslib 5.6 MB, dbscan 3.8 MB.

Depends (0)
none
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (1)
Author, Maintainer since 1.0.0 (2026)
Releases (1)
  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.0Latest
    2026-01-15 · 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

Cite

Cite this package

Run in R for the authors' entry:

citation("autoFlagR")

The package provides a citation file, so citation() returns the authors' own entry.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for autoFlagR version 1.0.0 [Data set]. HJJB, LLC. Data release v2026-10-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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