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 201–210 of 703 papers

Title	Date	Tasks	Status
Deep Sequence Modeling for Anomalous ISP Traffic Prediction	May 3, 2022	Outlier DetectionPrediction	—Unverified
Detect Professional Malicious User with Metric Learning in Recommender Systems	May 19, 2022	Metric LearningOutlier Detection	—Unverified
Cluster Purging: Efficient Outlier Detection based on Rate-Distortion Theory	Feb 22, 2023	ClusteringData Compression	—Unverified
A Non-Parametric Control Chart For High Frequency Multivariate Data	Jul 25, 2016	Outlier DetectionVocal Bursts Intensity Prediction	—Unverified
Toward Scalable and Unified Example-based Explanation and Outlier Detection	Nov 11, 2020	Decision MakingOutlier Detection	—Unverified
DEK-Forecaster: A Novel Deep Learning Model Integrated with EMD-KNN for Traffic Prediction	Jun 6, 2023	Decision MakingDenoising	—Unverified
A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice?	Apr 3, 2021	Model SelectionOutlier Detection	—Unverified
Dense outlier detection and open-set recognition based on training with noisy negative images	Jan 22, 2021	Open Set LearningOutlier Detection	—Unverified
An Efficient Hashing-based Ensemble Method for Collaborative Outlier Detection	Jan 18, 2022	Outlier Detection	—Unverified
Clustering with Outlier Removal	Jan 5, 2018	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