ビットコインの取引データにおける違法取引と合法取引の分類問題の精度向上

抄録

Crypto asset (Virtual currency) transactions have long been in the limelight. Crypto assets use cryptography to achieve decentralized management by participants on the Internet. Since they can be used by an unspecified number of people and there is no intermediary in the transaction, they are often misused for money laundering and terrorist financing. In this study, we adapt various machine learning methods to ELLIPTIC DATA, which is BITCOIN transaction data used in many previous studies. As a first step, we examine parameter optimization of random forests, feature refinement, sampling methods, and so on...