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 111–120 of 703 papers

Title	Date	Tasks	Status	Hype
Efficient Generation of Hidden Outliers for Improved Outlier Detection	Feb 6, 2024	Outlier Detection	CodeCode Available	0
A Unified Framework for Center-based Clustering of Distributed Data	Feb 2, 2024	ClusteringOutlier Detection	—Unverified	0
A Novel Deep Learning Approach Featuring Graph-Based Algorithm for Cell Segmentation and Tracking	Jan 18, 2024	Cell DetectionCell Segmentation	CodeCode Available	0
Towards Predicting the Quality of Red Wine Using Novel Machine Learning Methods for Classification, Data Visualization and Analysis	Jan 18, 2024	Data VisualizationEnsemble Learning	CodeCode Available	0
Dimensionality-Aware Outlier Detection: Theoretical and Experimental Analysis	Jan 10, 2024	Outlier Detection	CodeCode Available	0
Outlier Ranking in Large-Scale Public Health Streams	Jan 2, 2024	Outlier Detection	—Unverified	0
Unsupervised Outlier Detection using Random Subspace and Subsampling Ensembles of Dirichlet Process Mixtures	Jan 1, 2024	Outlier DetectionVariational Inference	CodeCode Available	0
Data Augmentation for Supervised Graph Outlier Detection via Latent Diffusion Models	Dec 29, 2023	Data AugmentationDenoising	CodeCode Available	1
Enhancing Traffic Flow Prediction using Outlier-Weighted AutoEncoders: Handling Real-Time Changes	Dec 27, 2023	ManagementOutlier Detection	CodeCode Available	0
User Equipment Assisted Localization for 6G Integrated Sensing and Communication	Dec 20, 2023	Integrated sensing and communicationISAC	—Unverified	0

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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