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 271–280 of 703 papers

Title	Date	Tasks	Status	Hype
DeepCAVE: An Interactive Analysis Tool for Automated Machine Learning	Jun 7, 2022	AutoMLBIG-bench Machine Learning	CodeCode Available	3
Robust Flow-based Conformal Inference (FCI) with Statistical Guarantee	May 22, 2022	Conformal PredictionOutlier Detection	—Unverified	0
Detect Professional Malicious User with Metric Learning in Recommender Systems	May 19, 2022	Metric LearningOutlier Detection	—Unverified	0
ODBO: Bayesian Optimization with Search Space Prescreening for Directed Protein Evolution	May 19, 2022	Bayesian OptimizationExperimental Design	CodeCode Available	0
Defending Object Detectors against Patch Attacks with Out-of-Distribution Smoothing	May 18, 2022	BIG-bench Machine Learningobject-detection	—Unverified	0
Deep Sequence Modeling for Anomalous ISP Traffic Prediction	May 3, 2022	Outlier DetectionPrediction	—Unverified	0
Towards an Ensemble Regressor Model for Anomalous ISP Traffic Prediction	May 3, 2022	ManagementOutlier Detection	—Unverified	0
Improving the Robustness of Federated Learning for Severely Imbalanced Datasets	Apr 28, 2022	Federated Learningimbalanced classification	—Unverified	0
Performance Analysis of Out-of-Distribution Detection on Trained Neural Networks	Apr 26, 2022	Outlier DetectionOut-of-Distribution Detection	—Unverified	0
Capturing the Denoising Effect of PCA via Compression Ratio	Apr 22, 2022	ClusteringDenoising	—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