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 491–500 of 703 papers

Title	Date	Tasks	Status
A feature construction framework based on outlier detection and discriminative pattern mining	Jul 17, 2014	Dimensionality Reductionfeature selection	—Unverified
A Framework for Clustering Uncertain Data	Aug 1, 2015	ClusteringOutlier Detection	—Unverified
A Framework for Developing and Evaluating Word Embeddings of Drug-named Entity	Jul 1, 2018	Named Entity Recognition (NER)Outlier Detection	—Unverified
A General Framework for Density Based Time Series Clustering Exploiting a Novel Admissible Pruning Strategy	Dec 2, 2016	AstronomyClustering	—Unverified
A geometric framework for outlier detection in high-dimensional data	Jul 1, 2022	Anomaly DetectionOutlier Detection	—Unverified
A Hybrid Deep Feature-Based Deformable Image Registration Method for Pathology Images	Aug 16, 2022	Image RegistrationOutlier Detection	—Unverified
A Hybrid Intelligent Framework for Maximising SAG Mill Throughput: An Integration of Expert Knowledge, Machine Learning and Evolutionary Algorithms for Parameter Optimisation	Dec 18, 2023	Evolutionary Algorithmsfeature selection	—Unverified
A Joint Indoor WLAN Localization and Outlier Detection Scheme Using LASSO and Elastic-Net Optimization Techniques	Oct 18, 2016	Outlier DetectionPosition	—Unverified
A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice?	Apr 3, 2021	Model SelectionOutlier Detection	—Unverified
A Local Density-Based Approach for Local Outlier Detection	Jun 28, 2016	Density EstimationObject	—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