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Systems and methods for automatic extraction of classification training data

机译:用于自动提取分类培训数据的系统和方法

摘要

A method for training a multi-class classification model includes receiving training data corresponding to a plurality of classes. For each class in the plurality of classes, the method includes training a binary classification model configured to determine whether or not an observation of training data belongs to the class and for each observation of training data identified as belonging to the class, extracting one or more class identification features from the observation of training data based on activations of an intermediate attention layer in the binary classification model. A multi-class classification model is trained using the class identification features extracted for each of the plurality of classes.
机译:用于训练多级分类模型的方法包括接收对应于多个类的训练数据。对于多个类中的每个类,该方法包括训练二进制分类模型,该模型被配置为确定训练数据的观察是否属于类,并且每次观察识别为属于类的训练数据,提取一个或多个基于二进制分类模型中的中间注意层的激活来观察培训数据的类识别特征。使用针对多个类中的每一个提取的类识别特征来训练多级分类模型。

著录项

  • 公开/公告号US11010692B1

    专利类型

  • 公开/公告日2021-05-18

    原文格式PDF

  • 申请/专利权人 EXCEED AL LTD;

    申请/专利号US202117144264

  • 发明设计人 IGAL MAZOR;YARON ISMAH-MOSHE;

    申请日2021-01-08

  • 分类号G06N20;

  • 国家 US

  • 入库时间 2022-08-24 18:43:14

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