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Unsupervised Anomaly Detection in Digital Currency Trading: A Clustering and Density-Based Approach Using Bitcoin Data

  • Hariguna T
Journal of Current Research in Blockchain (2024) 1(1) 70-90
DOI: 10.47738/jcrb.v1i1.12
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Abstract

… the DBSCAN algorithm, which is well-suited for detecting … we seek to uncover clusters of varying shapes and densities that can … DBSCAN is particularly effective for identifying clusters of …

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Hariguna, T. (2024). Unsupervised Anomaly Detection in Digital Currency Trading: A Clustering and Density-Based Approach Using Bitcoin Data. Journal of Current Research in Blockchain, 1(1), 70–90. https://doi.org/10.47738/jcrb.v1i1.12

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