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 401–410 of 703 papers

Title	Date	Tasks	Status
Performance Analysis of Out-of-Distribution Detection on Various Trained Neural Networks	Mar 29, 2021	Outlier DetectionOut-of-Distribution Detection	—Unverified
ast2vec: Utilizing Recursive Neural Encodings of Python Programs	Mar 22, 2021	ClusteringOutlier Detection	CodeCode Available
Homophily Outlier Detection in Non-IID Categorical Data	Mar 21, 2021	feature selectionOutlier Detection	—Unverified
Fairness-aware Outlier Ensemble	Mar 17, 2021	FairnessFraud Detection	—Unverified
Impacts of the Numbers of Colors and Shapes on Outlier Detection: from Automated to User Evaluation	Mar 10, 2021	AttributeOutlier Detection	—Unverified
Symbiotic Hybrid Neural Network Watchdog For Outlier Detection	Feb 28, 2021	Outlier Detection	—Unverified
Tax Evasion Risk Management Using a Hybrid Unsupervised Outlier Detection Method	Feb 25, 2021	ClusteringFraud Detection	—Unverified
Elastic Similarity and Distance Measures for Multivariate Time Series	Feb 20, 2021	ClassificationDynamic Time Warping	CodeCode Available
Feature Engineering for Scalable Application-Level Post-Silicon Debugging	Feb 8, 2021	Feature EngineeringOutlier Detection	—Unverified
RECol: Reconstruction Error Columns for Outlier Detection	Feb 4, 2021	Outlier 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