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    • 3. 发明申请
    • STRUCTURED DIFFERENTIAL LEARNING
    • 结构差异学习
    • US20110040710A1
    • 2011-02-17
    • US12540738
    • 2009-08-13
    • Jonathan CONNELL
    • Jonathan CONNELL
    • G06F15/18G06N7/02G06N7/04G05B13/00
    • G06N99/005G05B13/028
    • A method and information processing system train a control system using structured differential learning. A set of features extracted from a set of input data is analyzed by a plurality of analyzing components. An output response is generated by each analyzing component in the plurality of analyzing components for each feature regarding whether the each feature has an acceptable value associated therewith relative to a value of the parameter associated with the each analyzing component. A confidence score is associated with the each output response. Each output response and each confidence score is combined into a single final output response and single final confidence score. An analyzing component is identified from the plurality of analyzing components that is a strongest candidate for generating an incorrect final output response based at least on the confidence score.
    • 一种方法和信息处理系统使用结构差分学习训练控制系统。 通过多个分析部件分析从一组输入数据中提取的一组特征。 输出响应由针对每个特征的多个分析组件中的每个分析组件生成,涉及每个特征是否具有与其相关联的参数值相关联的可接受值。 置信度分数与每个输出响应相关联。 每个输出响应和每个置信度得分被组合成单个最终输出响应和单个最终置信度得分。 从多个分析部件中识别分析部件,该分析部件是至少基于置信度分数来产生不正确的最终输出响应的最强候选者。