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 241–250 of 703 papers

Title	Date	Tasks	Status
A Probabilistic Transformation of Distance-Based Outliers	May 16, 2023	Anomaly DetectionOutlier Detection	CodeCode Available
Efficient Neural Network based Classification and Outlier Detection for Image Moderation using Compressed Sensing and Group Testing	May 12, 2023	compressed sensingEfficient Neural Network	—Unverified
Outlier galaxy images in the Dark Energy Survey and their identification with unsupervised machine learning	May 2, 2023	Outlier Detection	—Unverified
Two-phase Dual COPOD Method for Anomaly Detection in Industrial Control System	Apr 30, 2023	Anomaly DetectionOutlier Detection	—Unverified
HPSCAN: Human Perception-Based Scattered Data Clustering	Apr 27, 2023	ClusteringOutlier Detection	CodeCode Available
Analyzing categorical time series with the R package ctsfeatures	Apr 24, 2023	ClusteringOutlier Detection	—Unverified
Ordinal time series analysis with the R package otsfeatures	Apr 24, 2023	ClusteringOutlier Detection	—Unverified
One-Class SVM on siamese neural network latent space for Unsupervised Anomaly Detection on brain MRI White Matter Hyperintensities	Apr 17, 2023	Anomaly DetectionLesion Detection	—Unverified
An Improved Heart Disease Prediction Using Stacked Ensemble Method	Apr 12, 2023	DiagnosticDisease Prediction	—Unverified
PIKS: A Technique to Identify Actionable Trends for Policy-Makers Through Open Healthcare Data	Apr 5, 2023	Outlier 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