AI-Driven Anomaly Detection for Data Quality
Overview
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.
Version 1.0.0 (2025-12-22)
Core Functionality
prep_for_anomaly(): Automated data preprocessing for anomaly detectionscore_anomaly(): Anomaly scoring using Isolation Forest and Local Outlier Factorflag_top_anomalies(): Flagging records as anomalous based on threshold or contamination rategenerate_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
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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
- 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
Documentation
- 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
Repository
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.
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)
Dependencies
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- 1.0.0Latest2026-01-15 · current release
- RR 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
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