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 541–550 of 703 papers

Title	Date	Tasks	Status
Are Out-of-Distribution Detection Methods Effective on Large-Scale Datasets?	Oct 30, 2019	General Classificationimage-classification	—Unverified
A Review of Change of Variable Formulas for Generative Modeling	Aug 4, 2023	Bayesian InferenceDecoder	—Unverified
A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks	Oct 28, 2024	ImputationOutlier Detection	—Unverified
A review on outlier/anomaly detection in time series data	Feb 11, 2020	Anomaly DetectionOutlier Detection	—Unverified
A Robust AUC Maximization Framework with Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification	Mar 18, 2018	EEGElectroencephalogram (EEG)	—Unverified
A Robust Framework for Classifying Evolving Document Streams in an Expert-Machine-Crowd Setting	Oct 6, 2016	ClusteringConstrained Clustering	—Unverified
A Robust Learning Algorithm for Regression Models Using Distributionally Robust Optimization under the Wasserstein Metric	Jun 7, 2017	Outlier Detectionregression	—Unverified
A Robust Regression Approach for Robot Model Learning	Aug 23, 2019	modelOutlier Detection	—Unverified
A Scalable Approach for Outlier Detection in Edge Streams Using Sketch-based Approximations	May 7, 2016	Anomaly DetectionAnomaly Detection in Edge Streams	—Unverified
A Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Industrial Wireless Sensor Networks	Jul 20, 2022	ClusteringOutlier Detection	—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