Supervised learning method for noise label, data classification processing method and device

A supervised learning and labeling technology, which is applied to instruments, character and pattern recognition, computer components, etc., can solve problems such as inaccurate labeling of samples and noisy labels

Inactive Publication Date: 2019-12-06
上海数禾信息科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] The main purpose of this application is to provide a supervised learning method for noise labels, a data

Method used

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  • Supervised learning method for noise label, data classification processing method and device
  • Supervised learning method for noise label, data classification processing method and device
  • Supervised learning method for noise label, data classification processing method and device

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Embodiment Construction

[0034] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiment of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the application. Obviously, the described embodiment is only It is an embodiment of a part of the application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0035] It should be noted that the terms "first" and "second" in the specification and claims of the present application and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific order or sequence. It should be understood that the data so used may be interchanged under appropriate circumstances for ...

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Abstract

The invention discloses a supervised learning method for noise tags, a data classification processing method and device. The method comprises the following steps: determining a first loss function fora classification model, and constructing a second loss function according to the loss function; and replacing the first loss function with the second loss function, and training the classification model according to the second loss function. According to the invention, the technical problem that noise tags exist due to inaccurate sample tag labeling is solved. According to the invention, the tolerance degree of the label quality is improved, and the labeling cost is reduced.

Description

technical field [0001] The present application relates to the field of machine learning, in particular, to a supervised learning method and device for noise labels, a data classification processing method and device. Background technique [0002] Classification is an important area of ​​extensive research and application in machine learning. As supervised learning, it is necessary to learn effectively based on data with class labels, so as to obtain a model that can accurately predict unlabeled samples. Therefore, the accuracy of sample labels is of paramount importance. [0003] The inventors found that if all sample labels are manually labeled by experts, the efficiency is low and the cost is high. However, it is difficult to guarantee the quality if crowdsourcing of labeling tasks is used. [0004] Aiming at the problem of inaccurate sample label labeling and noise labels in related technologies, no effective solution has been proposed so far. Contents of the inventi...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/24G06F18/214
Inventor 董雅洁
Owner 上海数禾信息科技有限公司
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