Fast feature selection method and system for maximum entropy modeling
    1.
    发明授权
    Fast feature selection method and system for maximum entropy modeling 有权
    快速特征选择方法和最大熵建模系统

    公开(公告)号:US07324927B2

    公开(公告)日:2008-01-29

    申请号:US10613366

    申请日:2003-07-03

    IPC分类号: G06F17/10

    摘要: A method to select features for maximum entropy modeling in which the gains for all candidate features are determined during an initialization stage and gains for only top-ranked features are determined during each feature selection stage. The candidate features are ranked in an ordered list based on the determined gains, a top-ranked feature in the ordered list with a highest gain is selected, and the model is adjusted using the selected top-ranked feature.

    摘要翻译: 选择用于最大熵建模的特征的方法,其中在初始化阶段期间确定所有候选特征的增益,并且在每个特征选择阶段期间确定仅顶级特征的增益。 基于所确定的增益,候选特征被排列在有序列表中,选择具有最高增益的有序列表中的排名最高的特征,并且使用所选择的顶级特征来调整模型。

    Fast feature selection method and system for maximum entropy modeling
    2.
    发明申请
    Fast feature selection method and system for maximum entropy modeling 有权
    快速特征选择方法和最大熵建模系统

    公开(公告)号:US20050021317A1

    公开(公告)日:2005-01-27

    申请号:US10613366

    申请日:2003-07-03

    IPC分类号: G06F20060101 G06F17/10

    摘要: A method to select features for maximum entropy modeling in which the gains for all candidate features are determined during an initialization stage and gains for only top-ranked features are determined during each feature selection stage. The candidate features are ranked in an ordered list based on the determined gains, a top-ranked feature in the ordered list with a highest gain is selected, and the model is adjusted using the selected using the top-ranked feature.

    摘要翻译: 选择用于最大熵建模的特征的方法,其中在初始化阶段期间确定所有候选特征的增益,并且在每个特征选择阶段期间确定仅顶级特征的增益。 基于所确定的增益,候选特征被排列在有序列表中,选择具有最高增益的有序列表中的排名最高的特征,并且使用排名最高的特征使用选择来调整模型。