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 261–270 of 703 papers

Title	Date	Tasks	Status
Finding Inner Outliers in High Dimensional Space	May 5, 2014	Outlier DetectionVocal Bursts Intensity Prediction	—Unverified
Choquet-Based Fuzzy Rough Sets	Feb 22, 2022	BIG-bench Machine LearningOutlier Detection	—Unverified
Characterizing Malicious Edges targeting on Graph Neural Networks	Sep 27, 2018	Graph GenerationLink Prediction	—Unverified
Anomaly Detection with HMM Gauge Likelihood Analysis	Jun 14, 2019	Anomaly DetectionClustering	—Unverified
Implications of Distance over Redistricting Maps: Central and Outlier Maps	Mar 2, 2022	FairnessOutlier Detection	—Unverified
Centering the Margins: Outlier-Based Identification of Harmed Populations in Toxicity Detection	May 24, 2023	Outlier Detection	—Unverified
A Hybrid Intelligent Framework for Maximising SAG Mill Throughput: An Integration of Expert Knowledge, Machine Learning and Evolutionary Algorithms for Parameter Optimisation	Dec 18, 2023	Evolutionary Algorithmsfeature selection	—Unverified
Findings of the WMT 2018 Shared Task on Parallel Corpus Filtering	Oct 1, 2018	Machine TranslationOutlier Detection	—Unverified
Flexible categorization using formal concept analysis and Dempster-Shafer theory	Aug 23, 2024	Outlier Detection	—Unverified
Cascade Watchdog: A Multi-tiered Adversarial Guard for Outlier Detection	Aug 20, 2021	Outlier DetectionOut-of-Distribution 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