Data stream classification method and device

A classification method and data flow technology, applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems of concept drift, affecting the accuracy of data flow classification, etc., to improve sensitivity, efficiency, and accuracy. Effect

Pending Publication Date: 2022-03-04
PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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Problems solved by technology

[0003] However, due to the characteristics of continuous noise, fast arrival, and unlimited mass of data streams, traditional static data mining algorithms no longer meet the requi

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  • Data stream classification method and device

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Embodiment Construction

[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0050] In order to facilitate the understanding of the technical solutions disclosed in the present invention, first a brief introduction to terms and concepts that may be involved in this application:

[0051] For a continuous data stream sample sequence x 1 ,x 2 ,...,x t-1 ,x t ,x t+1 ,..., t represents the time variable, s represents the sample attribute, m represents the number of sample attributes, and y represents the corresponding category of the ...

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Abstract

According to the data stream classification method and device, the concept drift state is accurately recognized according to the classification error rate of the integrated classifier at the current moment and the concept drift detection threshold value, the data window at the next moment is flexibly set according to the concept drift state, and if the data window is rapidly increased when concept drift does not occur, the data window can be rapidly increased. The data stream classification efficiency is improved; when it is not determined whether concept drift occurs or not, the increasing amplitude of a data window is reduced, whether concept drift occurs or not is further determined, and the influence of noise on classification accuracy is reduced; when concept drift occurs, a data window is quickly reduced, the sensitivity to sudden change type concept drift is improved, and the integrated classifier is quickly adjusted, so that the accuracy of data stream classification by the integrated classifier is integrally improved.

Description

technical field [0001] The present invention relates to the field of machine learning and data processing technology, and more specifically, to a method and device for classifying data streams. Background technique [0002] With the rapid development of information technology and the advent of the era of big data, data stream classification and recognition technology has become an important topic in the field of data mining, and is widely used in various fields such as sensor network target detection, Internet data recognition, and e-commerce decision-making. [0003] However, due to the characteristics of continuous noise, fast arrival, and unlimited mass of data streams, traditional static data mining algorithms no longer meet the requirements of practical applications, and changes in implicit knowledge or concepts in data streams will also lead to concept drift. Affects the accuracy of data stream classification. Contents of the invention [0004] In view of this, the ...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/24
Inventor 陈迎春冉晓旻董芳刘广怡孙昱莫有权王晓梅张静余道杰
Owner PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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