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
Image Modeling with Deep Convolutional Gaussian Mixture Models	Apr 19, 2021	ClusteringOutlier Detection	—Unverified
Impacts of the Numbers of Colors and Shapes on Outlier Detection: from Automated to User Evaluation	Mar 10, 2021	AttributeOutlier Detection	—Unverified
Improving Solar Flare Prediction by Time Series Outlier Detection	Jun 14, 2022	Outlier DetectionPrediction	—Unverified
Improving the Robustness of Federated Learning for Severely Imbalanced Datasets	Apr 28, 2022	Federated Learningimbalanced classification	—Unverified
Incremental Outlier Detection Modelling Using Streaming Analytics in Finance & Health Care	May 17, 2023	Diabetes PredictionFraud Detection	—Unverified
Integer Programming Relaxations for Integrated Clustering and Outlier Detection	Mar 6, 2014	ClusteringOutlier Detection	—Unverified
Interpretable Outlier Summarization	Mar 11, 2023	Anomaly DetectionOutlier Detection	—Unverified
Interpreting Outliers in Time Series Data through Decoding Autoencoder	Sep 3, 2024	Anomaly DetectionExplainable artificial intelligence	—Unverified
Interpreting Outliers: Localized Logistic Regression for Density Ratio Estimation	Feb 21, 2017	Density Ratio EstimationOutlier Detection	—Unverified
IoT-Based Environmental Control System for Fish Farms with Sensor Integration and Machine Learning Decision Support	Nov 7, 2023	Feature EngineeringImputation	—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