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Deep learning network and method and device for predicting missing data of deep learning network

A deep learning network and missing data technology, applied in the field of deep learning network and its missing data prediction, can solve the problems of low data accuracy, difficulty in meeting actual needs, and inability to reflect a change in missing values, so as to improve accuracy Effect

Pending Publication Date: 2022-04-22
上海皓桦科技股份有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, the missing algorithm often has a unique complement value for the missing value, which cannot reflect a possible change of the missing value
Therefore, the accuracy of the missing data predicted by the existing technology is low, which is difficult to meet the actual needs

Method used

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  • Deep learning network and method and device for predicting missing data of deep learning network
  • Deep learning network and method and device for predicting missing data of deep learning network
  • Deep learning network and method and device for predicting missing data of deep learning network

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Embodiment Construction

[0029] Some embodiments of the present invention are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention, and are not intended to limit the protection scope of the present invention.

[0030] In the description of the present invention, "module" and "processor" may include hardware, software or a combination of both. A module may include hardware circuits, various suitable sensors, communication ports, memory, and may also include software parts, such as program codes, or a combination of software and hardware. The processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor or any other suitable processor. The processor has data and / or signal processing functions. The processor can be implemented in software, hardware or a combination of both. The non-transitory computer readabl...

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Abstract

The invention relates to the technical field of learning networks, particularly provides a deep learning network and a missing data prediction method and device thereof, and aims to solve the problem of low accuracy of missing data predicted in the prior art. In order to achieve the purpose, the deep learning network comprises a vector extraction layer, a data coding layer, a feature fusion layer, a feature decoding layer and a data prediction layer. Through the deep learning network, the missing data corresponding to the input data can be obtained, the accuracy of the obtained missing data is improved, the support for the missing proportion of any input data is realized, the method is suitable for predicting any missing data, and the actual requirements of users are met.

Description

technical field [0001] The invention relates to the technical field of learning networks, and specifically provides a deep learning network and a method and device for predicting missing data. Background technique [0002] At present, many data in the real world are often incomplete and have missing values. Traditional non-neural network-based methods are often too weak to discover the laws in the data, and it is difficult to apply when the number is large. Methods based on deep learning often need to design a special network structure for specific data, which is fixed for the size of the input. The Transformer-based deep learning method removes a fixed proportion of input to train the network, but in the task of data completion, the proportion of missing values ​​​​in the input data is often not fixed. In addition, the missing algorithm often has a unique complement value for the missing value, which cannot reflect a possible change of the missing value. Therefore, the a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/215G06N3/04
CPCG06F16/215G06N3/045
Inventor 冯建兴
Owner 上海皓桦科技股份有限公司