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 231–240 of 703 papers

Title	Date	Tasks	Status
Anomaly-Injected Deep Support Vector Data Description for Text Outlier Detection	Oct 27, 2021	Anomaly DetectionOutlier Detection	—Unverified
Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation	Apr 28, 2021	Gaussian ProcessesImage Segmentation	—Unverified
Automatic Outlier Rectification via Optimal Transport	Mar 21, 2024	Outlier Detection	—Unverified
A New Approach To Two-View Motion Segmentation Using Global Dimension Minimization	Apr 10, 2013	ClusteringMotion Segmentation	—Unverified
An Improved Heart Disease Prediction Using Stacked Ensemble Method	Apr 12, 2023	DiagnosticDisease Prediction	—Unverified
DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection	Dec 15, 2022	Anomaly DetectionIntrusion Detection	—Unverified
Closed-Form, Provable, and Robust PCA via Leverage Statistics and Innovation Search	Jun 23, 2021	ClusteringForm	—Unverified
Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions	Apr 8, 2021	Outlier DetectionOut of Distribution (OOD) Detection	—Unverified
Adaptive Outlier Detection for Power MOSFETs Based on Gaussian Process Regression	Jan 25, 2022	GPROutlier Detection	—Unverified
A boosted outlier detection method based on the spectrum of the Laplacian matrix of a graph	Aug 7, 2020	ClusteringOutlier 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