infinite-dataset-hub/PaymentAnomalyScan

PaymentAnomalyScan数据集是一个经过策划的金融交易集合，包含标注欺诈活动可能性的标签。该数据集旨在训练机器学习模型，用于检测支付模式中的异常。数据集中的每条记录代表一笔独特的交易，并包括在欺诈检测中常用的多种特征，如交易金额、商户类别、位置以及用户行为模式。数据集包含正常交易和被标记为潜在欺诈的交易。标签为Normal表示典型交易，Fraud表示表现出可能欺诈活动的异常特征交易。

The PaymentAnomalyScan dataset is a curated collection of financial transactions with labels indicating the likelihood of fraudulent activity. This dataset is tailored for training machine learning models to detect anomalies in payment patterns. Each record in the dataset represents a unique transaction and includes a variety of features commonly used in fraud detection, such as transaction amount, merchant category, location, and user behavior patterns. The dataset includes both normal transactions and transactions flagged as potential fraud. Labels in the dataset are Normal for typical transactions and Fraud for transactions that exhibit unusual characteristics that could indicate fraudulent activity.