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 461–470 of 703 papers

Title	Date	Tasks	Status	Hype
PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning	Mar 12, 2020	BIG-bench Machine LearningOutlier Detection	—Unverified	0
SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection	Mar 11, 2020	Dimensionality ReductionFraud Detection	CodeCode Available	1
Hardware Architecture Proposal for TEDA algorithm to Data Streaming Anomaly Detection	Mar 8, 2020	Anomaly DetectionOutlier Detection	—Unverified	0
RCC-Dual-GAN: An Efficient Approach for Outlier Detection with Few Identified Anomalies	Mar 7, 2020	Outlier Detection	—Unverified	0
A review on outlier/anomaly detection in time series data	Feb 11, 2020	Anomaly DetectionOutlier Detection	—Unverified	0
SUOD: Toward Scalable Unsupervised Outlier Detection	Feb 8, 2020	Knowledge DistillationOutlier Detection	CodeCode Available	1
Statistical Outlier Identification in Multi-robot Visual SLAM using Expectation Maximization	Feb 7, 2020	Outlier DetectionSimultaneous Localization and Mapping	—Unverified	0
Detection of Thin Boundaries between Different Types of Anomalies in Outlier Detection using Enhanced Neural Networks	Jan 24, 2020	Anomaly DetectionOutlier Detection	—Unverified	0
Outlier Detection Ensemble with Embedded Feature Selection	Jan 15, 2020	feature selectionOutlier Detection	—Unverified	0
Explainable outlier detection through decision tree conditioning	Jan 2, 2020	Outlier Detection	CodeCode Available	1

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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