LARGE-SCALE ANOMALY DETECTION WITH RELATIVE DENSITY-RATIO ESTIMATION
    2.
    发明申请
    LARGE-SCALE ANOMALY DETECTION WITH RELATIVE DENSITY-RATIO ESTIMATION 审中-公开
    具有相对密度比估计的大规模异常检测

    公开(公告)号:US20160253598A1

    公开(公告)日:2016-09-01

    申请号:US14634515

    申请日:2015-02-27

    Applicant: Yahoo! Inc.

    CPC classification number: G06N20/00 G06F21/552

    Abstract: In one embodiment, a set of training data consisting of inliers may be obtained. A supervised classification model may be trained using the set of training data to identify outliers. The supervised classification model may be applied to generate an anomaly score for a data point. It may be determined whether the data point is an outlier based, at least in part, upon the anomaly score.

    Abstract translation: 在一个实施例中,可以获得由内联组成的一组训练数据。 可以使用该组训练数据来训练监督分类模型以识别异常值。 可以应用监督分类模型来产生数据点的异常得分。 可以至少部分地基于异常评分来确定数据点是否是异常值。

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