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
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Outlier detection algorithm based on k-nearest neighbors-local outlier factor
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
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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
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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
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Automatic Detection of Age-Related Macular Degeneration Based on Deep Learning and Local Outlier Factor Algorithm [PDF]
Diagnostics, 2022 Age-related macular degeneration (AMD) is a retinal disorder affecting the elderly, and society’s aging population means that the disease is becoming increasingly prevalent. The vision in patients with early AMD is usually unaffected or nearly normal but
Tingting He, Qiaoer Zhou, Yuanwen Zou
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Outlier Detection and Explanation Method Based on FOLOF Algorithm [PDF]
EntropyOutlier mining constitutes an essential aspect of modern data analytics, focusing on the identification and interpretation of anomalous observations. Conventional density-based local outlier detection methodologies frequently exhibit limitations due to ...
Lei Bai, Jiasheng Wang, Yu Zhou
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Local outlier factor algorithm based on correction of bidirectional neighbor
Tongxin xuebao, 2020 A local outlier factor algorithm based on bidirectional neighbor correction was proposed to solve the problems of existing outlier detection algorithms such as difficulty in parameter selection,poor efficiency and low accuracy.The bidirectional neighbor ...
Xiaohui YANG, Xiaoming LIU
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Using local outlier factor to detect fraudulent claims in auto insurance [PDF]
Mathematics and Modeling in Finance, 2022 Given the significant increase in fraudulent claims and the resulting financial losses, it is important to adopt a scientific approach to detect and prevent such cases.
Maryam Esna-Ashari +2 more
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Clustering-Based Outlier Detection Technique Using PSO-KNN
Journal of Applied Science and Engineering, 2023 In this work, we present an unsupervised machine learning algorithm for outlier detection by integrating Particle Swarm Optimization (PSO) and the K-nearest neighbor (KNN) technique.
Sushilata D. Mayanglambam +2 more
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The Network Link Outlier Factor (NLOF) for Fault Localization [PDF]
IEEE Open Journal of the Communications Society, 2020 We describe and experimentally evaluate the performance of our Network Link Outlier Factor (NLOF) for locating faults in communication networks. The NLOF is a unique outlier score assigned to each link in a network. It is computed using four distinct stages in a data analytics pipeline.
Christopher Mendoza, Michael P. Mcgarry
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