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 351–360 of 703 papers

Title	Date	Tasks	Status	Hype
Outlier detection in multivariate functional data through a contaminated mixture model	Jun 14, 2021	Outlier Detection	CodeCode Available	1
InFlow: Robust outlier detection utilizing Normalizing Flows	Jun 10, 2021	Density EstimationOutlier Detection	CodeCode Available	1
Partial Wasserstein and Maximum Mean Discrepancy distances for bridging the gap between outlier detection and drift detection	Jun 9, 2021	Drift DetectionNovelty Detection	CodeCode Available	0
Deep Clustering based Fair Outlier Detection	Jun 9, 2021	AttributeClustering	CodeCode Available	1
Safeguarding against spurious AI-based predictions: The case of automated verbal memory assessment	Jun 1, 2021	AttributeInductive Bias	—Unverified	0
Weighting vectors for machine learning: numerical harmonic analysis applied to boundary detection	Jun 1, 2021	BIG-bench Machine LearningBoundary Detection	—Unverified	0
OpenMatch: Open-set Consistency Regularization for Semi-supervised Learning with Outliers	May 28, 2021	Novelty DetectionOutlier Detection	CodeCode Available	1
Do We Really Need to Learn Representations from In-domain Data for Outlier Detection?	May 19, 2021	Outlier DetectionRepresentation Learning	—Unverified	0
Autoencoding Under Normalization Constraints	May 12, 2021	Outlier Detection	CodeCode Available	1
Towards a Model for LSH	May 11, 2021	Clusteringmodel	—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