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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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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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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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
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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
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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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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
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TADILOF: Time Aware Density-Based Incremental Local Outlier Detection in Data Streams
Sensors, 2020 Outlier detection in data streams is crucial to successful data mining. However, this task is made increasingly difficult by the enormous growth in the quantity of data generated by the expansion of Internet of Things (IoT).
Jen-Wei Huang +2 more
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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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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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