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公开(公告)号：US06950812B2
公开(公告)日：2005-09-27
申请号：US09954755
申请日：2001-09-17
CPC分类号： G06K9/6292
摘要： A method for determining accuracy of a classifier which provides an indication of the degree of correctness of the classifier rather than a mere correct/incorrect indication. The accuracy of the classifier is determined by determining a set of categories of an arrangement of categories selected for an item by the classifier and determining a set of categories of the arrangement selected for the item by an authoritative classifier. An accuracy measure which indicates a degree of correctness of the classifier is then determined based on the categories selected by the classifier and the categories selected by the authoritative classifier.
摘要翻译： 一种用于确定分类器的精度的方法，其提供分类器的正确程度的指示，而不是仅仅是正确/不正确的指示。 分类器的准确性通过确定由分类器为一个项目选择的类别排列的类别集合来确定，并由权威分类器确定为该项目选择的排列的一组类别。 然后，基于由分类器选择的类别和由权威分类器选择的类别来确定表示分类器的正确程度的精度度量。
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公开(公告)号：US5790645A
公开(公告)日：1998-08-04
申请号：US691885
申请日：1996-08-01
摘要： A technique for automatically designing a fraud detection system using a series of machine learning methods. Data mining and constructive induction are combined with more standard machine learning techniques to design methods for detecting fraudulent usage based on profiling customer behavior. Specifically, a rule-learning is used to uncover indicators of fraudulent behavior from a large user database. These indicators are used to create profilers, which then serve as features to the fraud detection system that combines evidence from multiple profilers to generate high-confidence intervention activities when the system is deployed on-line with user data.
摘要翻译： 一种使用一系列机器学习方法自动设计欺诈检测系统的技术。 数据挖掘和建设性归纳结合更多的标准机器学习技术，基于对客户行为的分析来设计检测欺诈性使用的方法。 具体来说，规则学习用于从大型用户数据库中发现欺诈行为的指标。 这些指标用于创建分析器，然后作为欺诈检测系统的特征，将系统与用户数据联机部署在一起，将来自多个分析器的证据组合起来，以产生高可信度的干预活动。
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