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Error sample identification method and device

An error sample and identification method technology, applied in the field of error sample identification methods and devices, can solve problems such as low efficiency, and achieve the effect of high-efficiency identification

Active Publication Date: 2020-02-07
BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] However, in the case of a large number of samples, it is very inefficient to manually identify the wrong samples in the wrong samples.

Method used

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  • Error sample identification method and device
  • Error sample identification method and device
  • Error sample identification method and device

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Embodiment Construction

[0023] The application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain related inventions, rather than to limit the invention. It should also be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings.

[0024] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and embodiments.

[0025] figure 1 An exemplary system architecture 100 to which embodiments of the error sample identification method or apparatus of the present application can be applied is shown.

[0026] like figure 1 As shown, the system architecture 100 may include terminal devices 10...

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Abstract

The application discloses an error sample recognition method and device. A specific implementation way of the method comprises the following steps: acquiring input information, obtaining at least one first classification corresponding to the input text and a first probability value corresponding to the first classification through a logic regression model to which the input text belongs; obtaining at least one first classification corresponding to the input text and a second probability value corresponding to the first classification through at least one associated logic regression model in response to a situation that each first probability value in at least one first probability value is less than a first preset threshold value; and recognizing the input text as the error sample of the logic regression model to which the input text belongs in response to the situation that the maximum second probability value in at least one second probability value is greater than the second preset threshold value. The error sample can be efficiently recognized by using the implementation way disclosed by the invention.

Description

technical field [0001] The present application relates to the field of computer technology, specifically to the field of machine learning technology, and in particular to a method and device for identifying error samples. Background technique [0002] Machine learning is the use of some methods to enable machines to realize human learning behaviors in order to acquire new knowledge or skills, and reorganize existing knowledge structures to continuously improve their own performance. During the use of the logistic regression model trained by the machine learning method, some error samples (badcase) that do not meet the user's psychological expectations are often generated. In order to identify erroneous samples in the samples, the prior art usually uses manual identification. [0003] However, in the case of a large number of samples, it is very inefficient to manually identify the wrong samples in the wrong samples. Contents of the invention [0004] The purpose of this ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/35G06N5/02
CPCG06F16/35G06N5/025
Inventor 陶玮
Owner BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD