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Identifying Suspected Instances of Fraud Utilizing Machine Learning Predictive Classification Models that Minimize Manual Labor to Inspect Anomalies

机译：利用机器学习预测分类模型识别欺诈的涉嫌实例，这些分类模型可最大限度地减少体力劳动来检查异常

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作者
Andrews, Kyle.;
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作者单位

Utica College.;

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授予单位 Utica College.;
学科
学位 M.S.
年度 2021
页码 39 p.
总页数 39
原文格式 PDF
正文语种 eng
中图分类
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Identifying Suspected Instances of Fraud Utilizing Machine Learning Predictive Classification Models that Minimize Manual Labor to Inspect Anomalies

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