Outlier Detection

Outlier Detection is a task of identifying a subset of a given data set which are considered anomalous in that they are unusual from other instances. It is one of the core data mining tasks and is central to many applications. In the security field, it can be used to identify potentially threatening users, in the manufacturing field it can be used to identify parts that are likely to fail.

Source: Coverage-based Outlier Explanation

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 341–350 of 703 papers

Title	Date	Tasks	Status
A Practical Algorithm for Distributed Clustering and Outlier Detection	May 24, 2018	ClusteringOutlier Detection	—Unverified
Improving Solar Flare Prediction by Time Series Outlier Detection	Jun 14, 2022	Outlier DetectionPrediction	—Unverified
A Bayesian Ensemble for Unsupervised Anomaly Detection	Oct 24, 2016	Anomaly DetectionClustering	—Unverified
Incremental Outlier Detection Modelling Using Streaming Analytics in Finance & Health Care	May 17, 2023	Diabetes PredictionFraud Detection	—Unverified
Kernel Random Projection Depth for Outlier Detection	Jun 12, 2023	Outlier Detection	—Unverified
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach	May 8, 2025	Conformal PredictionImputation	—Unverified
Exact Subspace Segmentation and Outlier Detection by Low-Rank Representation	Sep 8, 2011	Outlier Detection	—Unverified
Evaluation of (Un-)Supervised Machine Learning Methods for GNSS Interference Classification with Real-World Data Discrepancies	Mar 31, 2025	Data AugmentationDomain Adaptation	—Unverified
Breakdown Point of Robust Support Vector Machine	Sep 3, 2014	Outlier DetectionSensitivity	—Unverified
Anomaly Detection for an E-commerce Pricing System	Feb 25, 2019	Anomaly DetectionModel Selection	—Unverified

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All datasets ECG5000 Balance scale_class 1 Breast cancer Wisconsin_class 2 Breast cancer Wisconsin_class 4 Fashion-MNIST Glass identification Heart-C Hepatitis Internet Ad Ionosphere_class b SKAB

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	VRAE+SVM	Accuracy	0.98	—	Unverified
2	F-t ALSTM-FCN	Accuracy	0.95	—	Unverified
3	GENDIS	Accuracy	0.94	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	99.03	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	37.62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	65.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PAE	AUROC	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	99.05	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIX	AUC	0.86	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIX	AUC-ROC	0.85	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIX	AUC-ROC	0.93	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	86.33	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LSTMCaps	Average F1	0.74	—	Unverified