AnoShift

AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection

Dataset Information
Modalities
Tabular, Time series
Introduced
2022
License
BSD-3
Homepage
Official Website
Contents

Overview

AnoShift is a large-scale anomaly detection benchmark, which focuses on splitting the test data based on its temporal distance to the training set, introducing three testing splits: IID, NEAR, and FAR. This testing scenario proves to capture the in-time performance degradation of anomaly detection methods for classical to masked language models.

AnoShift benchmark aims to enable a better estimate of the anomaly detection model’s performance, under natural distribution shifts that occur over time in the input, closer to the real-world performance, leading to more robust anomaly detection algorithms.

The benchmark is based on the Kyoto-2016 dataset (https://www.takakura.com/Kyoto_data/).

Variants: AnoShift

Associated Benchmarks

This dataset is used in 1 benchmark:

Recent Benchmark Submissions

Task Model Paper Date
Unsupervised Anomaly Detection ACR-NTL (zero-shot, test anomaly ratio=20%) Zero-Shot Anomaly Detection via Batch … 2023-02-15
Unsupervised Anomaly Detection ACR-DSVDD (zero-shot, anomaly ratio=20%) Zero-Shot Anomaly Detection via Batch … 2023-02-15
Unsupervised Anomaly Detection ACR-NTL (zero-shot, test anomaly ratio=1%) Zero-Shot Anomaly Detection via Batch … 2023-02-15
Unsupervised Anomaly Detection ACR-DSVDD (zero-shot, anomaly ratio=1%) Zero-Shot Anomaly Detection via Batch … 2023-02-15
Unsupervised Anomaly Detection ECOD Li et al. (2022) AnoShift: A Distribution Shift Benchmark … 2022-06-30
Unsupervised Anomaly Detection LOF AnoShift: A Distribution Shift Benchmark … 2022-06-30
Unsupervised Anomaly Detection LUNAR AnoShift: A Distribution Shift Benchmark … 2022-06-30
Unsupervised Anomaly Detection BERT AnoShift: A Distribution Shift Benchmark … 2022-06-30
Unsupervised Anomaly Detection IsoForest AnoShift: A Distribution Shift Benchmark … 2022-06-30
Unsupervised Anomaly Detection Internal Contrastive Learning AnoShift: A Distribution Shift Benchmark … 2022-06-30
Unsupervised Anomaly Detection deepSVDD AnoShift: A Distribution Shift Benchmark … 2022-06-30
Unsupervised Anomaly Detection AE for anomalies AnoShift: A Distribution Shift Benchmark … 2022-06-30
Unsupervised Anomaly Detection COPOD AnoShift: A Distribution Shift Benchmark … 2022-06-30
Unsupervised Anomaly Detection OC-SVM AnoShift: A Distribution Shift Benchmark … 2022-06-30
Unsupervised Anomaly Detection SO-GAAL AnoShift: A Distribution Shift Benchmark … 2022-06-30

Research Papers

Recent papers with results on this dataset:

External Links: