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 121–130 of 703 papers

Title	Date	Tasks	Status
AWT -- Clustering Meteorological Time Series Using an Aggregated Wavelet Tree	Dec 13, 2022	ClusteringOutlier Detection	—Unverified
Backdoor Defense in Federated Learning Using Differential Testing and Outlier Detection	Feb 21, 2022	backdoor defenseFederated Learning	—Unverified
A Robust AUC Maximization Framework with Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification	Mar 18, 2018	EEGElectroencephalogram (EEG)	—Unverified
BAHP: Benchmark of Assessing Word Embeddings in Historical Portuguese	Nov 1, 2021	Outlier DetectionWord Embeddings	—Unverified
AnoMalNet: Outlier Detection based Malaria Cell Image Classification Method Leveraging Deep Autoencoder	Mar 10, 2023	image-classificationImage Classification	—Unverified
Benchmarking Unsupervised Outlier Detection with Realistic Synthetic Data	Apr 15, 2020	BenchmarkingOutlier Detection	—Unverified
Analysis of Learning from Positive and Unlabeled Data	Dec 1, 2014	General ClassificationOutlier Detection	—Unverified
A deep mixture density network for outlier-corrected interpolation of crowd-sourced weather data	Jan 25, 2022	Outlier Detection	—Unverified
Choquet-Based Fuzzy Rough Sets	Feb 22, 2022	BIG-bench Machine LearningOutlier Detection	—Unverified
Clustering with Outlier Removal	Jan 5, 2018	ClusteringOutlier Detection	—Unverified

Show:10 25 50

← PrevPage 13 of 71Next →

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