coldrift: Lightweight Column Drift Detection for Tabular Data
Abstract
Provides simple and efficient methods to detect column-level data drift between reference and target datasets. Designed for monitoring tabular data pipelines and machine learning inputs using statistical distance measures.
Fields of Study & Subjects
Data Stream Mining Techniques
Fault Detection and Control Systems
Anomaly Detection Techniques and Applications
Publication details
- Publication date
- 29 January 2026
- Document type
- Dataset