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 531–540 of 703 papers

Title	Date	Tasks	Status
AI-enabled Blockchain: An Outlier-aware Consensus Protocol for Blockchain-based IoT Networks	Jun 17, 2019	BIG-bench Machine LearningOutlier Detection	—Unverified
An Outlier Detection-based Tree Selection Approach to Extreme Pruning of Random Forests	Mar 17, 2015	Ensemble PruningOutlier Detection	—Unverified
Applications of a Graph Theoretic Based Clustering Framework in Computer Vision and Pattern Recognition	Jan 7, 2018	Clusteringgeo-localization	—Unverified
Applications of Data Mining Techniques for Vehicular Ad hoc Networks	Jun 19, 2018	ClassificationClustering	—Unverified
A Practical Algorithm for Distributed Clustering and Outlier Detection	May 24, 2018	ClusteringOutlier Detection	—Unverified
A probabilistic view on Riemannian machine learning models for SPD matrices	May 5, 2025	Dimensionality ReductionOutlier Detection	—Unverified
Symbiotic Hybrid Neural Network Watchdog For Outlier Detection	Feb 28, 2021	Outlier Detection	—Unverified
A Rank-Based Similarity Metric for Word Embeddings	May 4, 2018	ClusteringOutlier Detection	—Unverified
A refined convergence analysis of pDCA_e with applications to simultaneous sparse recovery and outlier detection	Apr 19, 2018	compressed sensingCPU	—Unverified
Are Outlier Detection Methods Resilient to Sampling?	Jul 31, 2019	Outlier Detection	—Unverified

Show:10 25 50

← PrevPage 54 of 71Next →

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