Dataset for Classification of Suspicious Financial Transactions
收藏Zenodo2025-06-09 更新2026-05-26 收录
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https://zenodo.org/doi/10.5281/zenodo.15493391
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Abstract— This study investigates the application of machine learning models for detecting suspicious financial transactions. Utilizing a dataset of 12,571 transactions from PT Bank ABC, the research encompasses various stages such as data preprocessing, feature selection, and addressing class imbalance. The models evaluated include Random Forest, XGBoost, and SVM, which were assessed through cross-validation with StratifiedKFold and optimized using RandomizedSearchCV.
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Zenodo创建时间：
2025-05-23
