A Variable Markovian Based Outlier Detection Method for Multi-Dimensional Sequence over Data Stream

2016 ◽  
Author(s):  
Dongsheng Yang ◽  
Yijie Wang ◽  
Yongmou Li ◽  
Xingkong Ma
Keyword(s):  
Outlier Detection ◽  
Data Stream ◽  
Detection Method

scholarly journals Anomaly Pattern Detection in Streaming Data Based on the Transformation to Multiple Binary-Valued Data Streams

2021 ◽  
Vol 12 (1) ◽  
pp. 19-27
Author(s):  
Taegong Kim ◽  
Cheong Hee Park
Keyword(s):  
Outlier Detection ◽  
Data Streams ◽  
Data Stream ◽  
Detection Method ◽  
Binary Classification ◽  
Streaming Data ◽  
Pattern Detection ◽  
Detection Methods ◽  
Anomaly Pattern ◽  
Isolation Forest

Abstract Anomaly pattern detection in a data stream aims to detect a time point where outliers begin to occur abnormally. Recently, a method for anomaly pattern detection has been proposed based on binary classification for outliers and statistical tests in the data stream of binary labels of normal or an outlier. It showed that an anomaly pattern can be detected accurately even when outlier detection performance is relatively low. However, since the anomaly pattern detection method is based on the binary classification for outliers, most well-known outlier detection methods, with the output of real-valued outlier scores, can not be used directly. In this paper, we propose an anomaly pattern detection method in a data stream using the transformation to multiple binary-valued data streams from real-valued outlier scores. By using three outlier detection methods, Isolation Forest(IF), Autoencoder-based outlier detection, and Local outlier factor(LOF), the proposed anomaly pattern detection method is tested using artificial and real data sets. The experimental results show that anomaly pattern detection using Isolation Forest gives the best performance.

A new outlier detection method based on OPTICS

2019 ◽  
Vol 45 ◽  
pp. 197-212 ◽  
Author(s):  
Yue Fei Wang ◽  
Yu Jiong ◽  
Guo Ping Su ◽  
Yu Rong Qian
Keyword(s):  
Outlier Detection ◽  
Detection Method
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