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 411–420 of 703 papers

Title	Date	Tasks	Status
Simple robust genomic prediction and outlier detection for a multi-environmental field trial	Jul 19, 2018	Outlier DetectionPrediction	—Unverified
Single Channel Speech Enhancement Using Outlier Detection	May 4, 2016	Noise EstimationOutlier Detection	—Unverified
Size Matters: Cardinality-Constrained Clustering and Outlier Detection via Conic Optimization	May 22, 2017	ClusteringConstrained Clustering	—Unverified
Spatiotemporal Data Mining: A Survey on Challenges and Open Problems	Mar 31, 2021	ArticlesClustering	—Unverified
SPINEX: Similarity-based Predictions with Explainable Neighbors Exploration for Anomaly and Outlier Detection	Jul 5, 2024	Anomaly DetectionDensity Estimation	—Unverified
SSDBCODI: Semi-Supervised Density-Based Clustering with Outliers Detection Integrated	Aug 10, 2022	ClusteringOutlier Detection	—Unverified
STACC, OOV Density and N-gram Saturation: Vicomtech's Participation in the WMT 2018 Shared Task on Parallel Corpus Filtering	Oct 1, 2018	Machine TranslationOutlier Detection	—Unverified
Statistical Outlier Identification in Multi-robot Visual SLAM using Expectation Maximization	Feb 7, 2020	Outlier DetectionSimultaneous Localization and Mapping	—Unverified
Structured Group Sparsity: A Novel Indoor WLAN Localization, Outlier Detection, and Radio Map Interpolation Scheme	Oct 18, 2016	Indoor LocalizationOutlier Detection	—Unverified
Suppressing Outlier Reconstruction in Autoencoders for Out-of-Distribution Detection	Jan 1, 2021	Outlier DetectionOut-of-Distribution 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