Outlier detection algorithm based on k-nearest neighbors-local outlier factor [PDF]
Journal of Algorithms & Computational Technology, 2022 The main task of outlier detection is to detect data objects which have a different mechanism from the conventional data set. The existing outlier detection methods are mainly divided into two directions: local outliers and global outliers. Aiming at the
He Xu, Lin Zhang, Peng Li, Feng Zhu
doaj +4 more sources
Electricity Theft Detection in AMI Based on Clustering and Local Outlier Factor [PDF]
IEEE Access, 2021 As one of the key components of smart grid, advanced metering infrastructure (AMI) provides an immense number of data, making technologies such as data mining more suitable for electricity theft detection.
Yanlin Peng +6 more
doaj +4 more sources
Outlier Detection Credit Card Transactions Using Local Outlier Factor Algorithm (LOF)
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2019 Threats or fraud for credit card owners and banks as service providers have been harmed by the actions of perpetrators of credit card thieves. All transaction data are stored in the bank's database, but are limited in information and cannot be used as a ...
Silvano Sugidamayatno, Danang Lelono
doaj +5 more sources
A Review of Local Outlier Factor Algorithms for Outlier Detection in Big Data Streams [PDF]
Big Data and Cognitive Computing, 2020 Outlier detection is a statistical procedure that aims to find suspicious events or items that are different from the normal form of a dataset. It has drawn considerable interest in the field of data mining and machine learning.
Omar Alghushairy +3 more
doaj +2 more sources
Adaptable and Robust EEG Bad Channel Detection Using Local Outlier Factor (LOF) [PDF]
Sensors, 2022 Electroencephalogram (EEG) data are typically affected by artifacts. The detection and removal of bad channels (i.e., with poor signal-to-noise ratio) is a crucial initial step.
Velu Prabhakar Kumaravel +3 more
doaj +2 more sources
Affinity Propagation Based on Structural Similarity Index and Local Outlier Factor for Hyperspectral Image Clustering [PDF]
Remote Sensing, 2022 In hyperspectral remote sensing, the clustering technique is an important issue of concern. Affinity propagation is a widely used clustering algorithm.
Haimiao Ge +5 more
doaj +2 more sources
Automatic Detection of Age-Related Macular Degeneration Based on Deep Learning and Local Outlier Factor Algorithm. [PDF]
Diagnostics (Basel), 2022 He T, Zhou Q, Zou Y.
europepmc +3 more sources
An Efficient Density-Based Local Outlier Detection Approach for Scattered Data
IEEE Access, 2019 After the local outlier factor was first proposed, there is a large family of local outlier detection approaches derived from it. Since the existing approaches only focus on the extent of overall separation between an object and its neighbors, and ignore
Shubin Su +6 more
doaj +3 more sources
Spatial Outlier Detection of CO2 Monitoring Data Based on Spatial Local Outlier Factor
Journal of Engineering Science and Technology Review, 2015 Spatial local outlier factor (SLOF) algorithm was adopted in this study for spatial outlier detection because of the limitations of the traditional static threshold detection. Based on the spatial characteristics of CO 2 monitoring data obtained in the carbon capture and storage (CCS) project, the K-Nearest Neighbour (KNN) graph was constructed using ...
Xin Liu, Zhang Shaoliang, Zheng Pulin
+5 more sources
An Incremental Local Outlier Detection Method in the Data Stream
Applied Sciences, 2018 Outlier detection has attracted a wide range of attention for its broad applications, such as fault diagnosis and intrusion detection, among which the outlier analysis in data streams with high uncertainty and infinity is more challenging.
Haiqing Yao +3 more
doaj +3 more sources