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    • 2. 发明申请
    • METHOD AND SYSTEM FOR DEVELOPING A CLASSIFICATION TOOL
    • 用于开发分类工具的方法和系统
    • US20110119209A1
    • 2011-05-19
    • US12618181
    • 2009-11-13
    • Evan R. KirshenbaumGeorge FormanShyam Sundar Rajaram
    • Evan R. KirshenbaumGeorge FormanShyam Sundar Rajaram
    • G06F15/18G06N5/02
    • G06N5/02
    • An exemplary embodiment of the present invention provides a computer implemented method of developing a classifier. The method includes obtaining a set of training data comprising labeled cases. The method also includes training a classifier based, at least in part, on the training data. The method also includes applying the classifier to a plurality of unlabeled cases to generate classification scores for each of the unlabeled cases, wherein each classification score corresponds with an instance of a corresponding case. Furthermore, the classification score corresponding to a first instance in a case is computed based, at least in part, on a value of a case-centric feature corresponding to the first instance, wherein the value of the case-centric feature is based, at least in part, on characteristics of the first instance and a second instance in the case.
    • 本发明的示例性实施例提供了一种开发分类器的计算机实现方法。 该方法包括获得包括标记情况的一组训练数据。 该方法还包括至少部分地基于训练数据来训练分类器。 该方法还包括将分类器应用于多个未标记的情况以产生每个未标记情况的分类分数,其中每个分类分数对应于相应病例的实例。 此外,至少部分地基于与第一实例对应的以案例为中心的特征的值来计算与案例中的第一实例相对应的分类得分,其中以案例为中心的特征的值基于 至少部分是关于一审的特征和第二例的情况。
    • 7. 发明授权
    • Method and system for developing a classification tool
    • 开发分类工具的方法和系统
    • US08311957B2
    • 2012-11-13
    • US12618181
    • 2009-11-13
    • Evan R. KirshenbaumGeorge FormanShyam Sundar Rajaram
    • Evan R. KirshenbaumGeorge FormanShyam Sundar Rajaram
    • G06F15/18G06F17/00
    • G06N5/02
    • An exemplary embodiment of the present invention provides a computer implemented method of developing a classifier. The method includes obtaining a set of training data comprising labeled cases. The method also includes training a classifier based, at least in part, on the training data. The method also includes applying the classifier to a plurality of unlabeled cases to generate classification scores for each of the unlabeled cases, wherein each classification score corresponds with an instance of a corresponding case. Furthermore, the classification score corresponding to a first instance in a case is computed based, at least in part, on a value of a case-centric feature corresponding to the first instance, wherein the value of the case-centric feature is based, at least in part, on characteristics of the first instance and a second instance in the case.
    • 本发明的示例性实施例提供了一种开发分类器的计算机实现方法。 该方法包括获得包括标记情况的一组训练数据。 该方法还包括至少部分地基于训练数据来训练分类器。 该方法还包括将分类器应用于多个未标记的情况以产生每个未标记情况的分类分数,其中每个分类分数对应于相应病例的实例。 此外,至少部分地基于与第一实例对应的以案例为中心的特征的值来计算与案例中的第一实例相对应的分类分数,其中以案例为中心的特征的值基于 至少部分是关于一审的特征和第二例的情况。