In this paper, we first propose to use the maximum margin criterion to sift unknown outliers, which demonstrates superior performance. However, the resultant ...
Oct 22, 2024 · In this paper, we first propose to use the maximum margin criterion to sift unknown outliers from a given data set, which demonstrates superior ...
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What are the applications of outlier detection?
What is the purpose of outlier detection?
In this paper, we first propose to use the maximum margin criterion to sift unknown outliers, which demonstrates superior performance. However, the resultant ...
In this paper, we will present a structured and comprehensive review of the research on outlier detection. We have clustered existing methods into different ...
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Oct 22, 2024 · A number of surveys, research and review articles and books cover outlier detection techniques in machine learning and statistical domains ...
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Sep 11, 2024 · In this blog, we will understand what anomaly detection across financial transactions is, detection techniques, and how automated anomaly detection solutions ...
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Outlier detection is important in many applications in addition to fraud detection such as medical care, public safety and security, industry damage detection, ...
In this paper I propose the use of common machine learning algorithms (i.e. boosted trees, cross validation and cluster analysis) to determine the data ...
The banking and insurance sectors are advanced with respect to deployment, and ML is most often used in anti-money laundering and fraud-detection applications.
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In financial sectors, outlier detection helps in identifying fraud and unusual transactions, which are critical for maintaining the integrity of financial ...
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