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 501–510 of 703 papers

Title	Date	Tasks	Status
LOSDD: Leave-Out Support Vector Data Description for Outlier Detection	Dec 27, 2022	One-Class ClassificationOutlier Detection	—Unverified
Lower Dimensional Spherical Representation of Medium Voltage Load Profiles for Visualization, Outlier Detection, and Generative Modelling	Nov 21, 2024	ARCClustering	—Unverified
LS-VOS: Identifying Outliers in 3D Object Detections Using Latent Space Virtual Outlier Synthesis	Oct 2, 2023	3D Object DetectionAutonomous Driving	—Unverified
Machine learning based forecasting of significant daily returns in foreign exchange markets	Sep 21, 2020	BIG-bench Machine LearningOutlier Detection	—Unverified
Machine Learning for Complex Systems with Abnormal Pattern by Exception Maximization Outlier Detection Method	Jul 5, 2024	Anomaly DetectionOutlier Detection	—Unverified
Mathematical Models for Local Sensing Hashes	Nov 16, 2021	ClusteringOutlier Detection	—Unverified
MCODE: Multivariate Conditional Outlier Detection	May 15, 2015	General ClassificationOutlier Detection	—Unverified
Meta-learning for Positive-unlabeled Classification	Jun 6, 2024	ClassificationDensity Ratio Estimation	—Unverified
Meta-Learning for Relative Density-Ratio Estimation	Jul 2, 2021	Density Ratio EstimationMeta-Learning	—Unverified
Meta-Learning for Unsupervised Outlier Detection with Optimal Transport	Nov 1, 2022	Meta-LearningOutlier 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