Outliers and anomalies in training and testing datasets for AI-powered morphometry-evidence from CT scans of the spleen. [PDF]
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Optimizing Crop Yield Prediction: An In-Depth Analysis of Outlier Detection Algorithms on Davangere Region. [PDF]
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Application of Cluster-Based Local Outlier Factor Algorithm in Anti-Money Laundering
2009 International Conference on Management and Service Science, 2009Financial institutions’ capability in recognizing suspicious money laundering transactional behavioral patterns (SMLTBPs) is critical to anti-money laundering. Combining distance-based unsupervised clustering and local outlier detection, this paper designs a new cluster-based local outlier factor (CBLOF) algorithm to identify SMLTBPs and use authentic ...
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GMBLOF: A Machine Learning Algorithm of Novelty Detection Based on Local Outlier Factor
2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI), 2022Xing Yang +4 more
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Distributed filtering algorithm based on local outlier factor under data integrity attacks
Journal of the Franklin Institute, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A Genetic-Based Incremental Local Outlier Factor Algorithm for Efficient Data Stream Processing
Proceedings of the 2020 4th International Conference on Compute and Data Analysis, 2020Interest in outlier detection methods is increasing because detecting outliers is an important operation for many applications such as detecting fraud transactions in credit card, network intrusion detection and data analysis in different domains. We are now in the big data era, and an important type of big data is data stream.
Omar Alghushairy +3 more
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Accelerating the local outlier factor algorithm on a GPU for intrusion detection systems
Proceedings of the 3rd Workshop on General-Purpose Computation on Graphics Processing Units, 2010The Local Outlier Factor (LOF) is a very powerful anomaly detection method available in machine learning and classification. The algorithm defines the notion of local outlier in which the degree to which an object is outlying is dependent on the density of its local neighborhood, and each object can be assigned an LOF which represents the likelihood of
Malak Alshawabkeh +2 more
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A Comparative Study of Local Outlier Factor Algorithms for Outliers Detection in Data Streams
2018Outlier detection analyzes data, finds out anomalies, and helps to discover unforeseen activities in safety crucial systems. Outlier detection helps in early prediction of various fraudulent activities like credit card theft, fake insurance claim, tax stealing, real-time monitoring, medical systems, online transactions, and many more.
Supriya Mishra, Meenu Chawla
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In the era of big data, outlier detection has become an important task for many applications, such as the network intrusion detection system. Data streams are a unique type of big data, which recently has gained a lot of attention from researchers. Nevertheless, there are challenges in applying traditional outlier detection algorithms for data streams.
Omar Alghushairy +3 more
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Robust Anomaly Detection Using Local Outlier Factor and the Bayesian Bagged Clustering Algorithm
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