Active Learning in the Detection of Anomalies in Cryptocurrency Transactions
Leandro L. Cunha,
Miguel A. Brito,
Domingos F. Oliveira
et al.
Abstract:The cryptocurrency market has grown significantly, and this quick growth has given rise to scams. It is necessary to put fraud detection mechanisms in place. The challenge of inadequate labeling is addressed in this work, which is a barrier to the training of high-performance supervised classifiers. It aims to lessen the necessity for laborious and time-consuming manual labeling. Some unlabeled data points have labels that are more pertinent and informative for the supervised model to learn from. The viability… Show more
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