Feature extraction method and device, computer equipment and storage medium

A feature extraction and operator technology, applied in the computer field, can solve problems that affect the efficiency of feature extraction, consume a lot of time, and have different operators.

Active Publication Date: 2021-03-26
TENCENT TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, different network models or different sample data will lead to different operators used in feature extraction, which requires developers to code different feature extraction codes according to actual needs, which will consume more time and affect feature extraction efficiency.

Method used

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  • Feature extraction method and device, computer equipment and storage medium
  • Feature extraction method and device, computer equipment and storage medium
  • Feature extraction method and device, computer equipment and storage medium

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Embodiment Construction

[0072] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the following will further describe the embodiments of the present application in detail in conjunction with the accompanying drawings.

[0073] The terms "first", "second", etc. used in the present application may be used herein to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, a first node could be termed a second node, and, similarly, a second node could be termed a first node, without departing from the scope of the present application.

[0074] The terms "at least one", "multiple", "each" and "any" used in this application, at least one includes one, two or more than two, multiple includes two or more, and each A refers to each of the corresponding plurality, and any refers to any one of the plurality. For ex...

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Abstract

The embodiment of the invention discloses a feature extraction method and device, computer equipment and a storage medium, and belongs to the technical field of computers. The method comprises the following steps: obtaining a data configuration file, obtaining a feature extraction framework, calling the feature extraction framework based on the data configuration file, and executing the followingsteps: determining an operator matched with each association relationship type according to the association relationship type and the matching relationship between at least two first data tables, andcalling the operator, and performing feature extraction on the at least two first data tables to obtain feature information of the plurality of objects. According to the method provided by the embodiment of the invention, a universal feature extraction framework is provided, feature information of a plurality of objects contained in the data configuration file is automatically extracted through the feature extraction framework, a developer does not need to develop feature extraction codes for a network model, the time consumed for developing the feature extraction codes is reduced, therefore,the feature extraction efficiency is improved, and the data calculation of the data configuration file is realized.

Description

technical field [0001] The embodiments of the present application relate to the field of computer technology, and in particular to a feature extraction method, device, computer equipment, and storage medium. Background technique [0002] With the development of computer technology, the application of network model is more and more extensive. Usually, it is necessary to use the feature information of the sample data to train the network model, and the accuracy of the feature information has a great influence on the training effect of the network model. [0003] Usually, before training the network model, developers need to write feature extraction code, run the feature extraction code to obtain the feature information of the sample data, and then use the feature information to train the network model. [0004] However, different network models or different sample data will lead to different operators used in feature extraction, which requires developers to code different fea...

Claims

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Application Information

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IPC IPC(8): G06N20/00
CPCG06N20/00
Inventor 洪立涛陶淳苏函晶韩宝昌黄薇屹
Owner TENCENT TECH (SHENZHEN) CO LTD
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