分布式计算：大数据平台采用分布式计算架构，能够高效处理和存储大量数据。通过分布式计算，复杂的异常检测算法可以在短时间内完成计算，提高系统的响应速度。
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模型过拟合：检测模型可能在训练数据上表现良好，但在实际应用中效果不佳。过拟合问题需要通过交叉验证、正则化等技术来缓解。
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机器学习算法能够处理复杂的交易数据，捕捉隐藏的模式和异常特征，在实际应用中取得了显著效果。企业可以根据具体需求选择合适的算法，并结合专家知识进行模型优化和改进。
交货至指定地点：将货物运送至合同约定的买方场所或仓库，并承担目的地国内运输及派送费用。
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金融公司首先从不同的业务系统中收集交易数据，包括交易金额、交易时间、交易地点等信息。然后，他们对这些数据进行清洗和整合，以确保数据的准确性和完整性。
将货物运输至目的地的风险和费用（进口费用除外）：卖方负责将货物从起运地运送到买方指定的目的地，并承担运输途中的所有费用，包括运输费、保险费（如果投保的话）以及可能产生的各种风险。
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