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 641–650 of 703 papers

Title	Date	Tasks	Status	Hype
Deep-Anomaly: Fully Convolutional Neural Network for Fast Anomaly Detection in Crowded Scenes	Sep 3, 2016	Anomaly DetectionOutlier Detection	—Unverified	0
Multi-Person Pose Estimation with Local Joint-to-Person Associations	Aug 30, 2016	Keypoint DetectionMulti-Person Pose Estimation	CodeCode Available	0
Network Volume Anomaly Detection and Identification in Large-scale Networks based on Online Time-structured Traffic Tensor Tracking	Aug 19, 2016	Anomaly DetectionOutlier Detection	—Unverified	0
Outlier Detection on Mixed-Type Data: An Energy-based Approach	Aug 17, 2016	Outlier DetectionVocal Bursts Type Prediction	CodeCode Available	0
Find the word that does not belong: A Framework for an Intrinsic Evaluation of Word Vector Representations	Aug 1, 2016	Machine TranslationOutlier Detection	—Unverified	0
Robust Contextual Outlier Detection: Where Context Meets Sparsity	Jul 28, 2016	Outlier Detection	—Unverified	0
A Non-Parametric Control Chart For High Frequency Multivariate Data	Jul 25, 2016	Outlier DetectionVocal Bursts Intensity Prediction	—Unverified	0
Dealing with Class Imbalance using Thresholding	Jul 10, 2016	ClassificationGeneral Classification	—Unverified	0
LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection	Jul 1, 2016	Anomaly DetectionDecoder	CodeCode Available	2
A Local Density-Based Approach for Local Outlier Detection	Jun 28, 2016	Density EstimationObject	—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