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Method and system for obtaining concept drift amount of data distribution

A technology of concept drift and data distribution, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problem that the prediction results are no longer reliable and effective.

Pending Publication Date: 2020-09-04
TSINGHUA UNIV
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  • Summary
  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The emergence of concept drift may cause the prediction results of a model trained and deployed based on historical data in a certain field to no longer be credible and effective on new data. Therefore, a reliable method and system are needed to obtain the degree of concept drift for measuring data distribution.

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  • Method and system for obtaining concept drift amount of data distribution
  • Method and system for obtaining concept drift amount of data distribution
  • Method and system for obtaining concept drift amount of data distribution

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Embodiment Construction

[0013] The following description includes exemplary methods, systems, techniques and instruction sequences that embody the techniques of the present invention. However, it should be understood that the described invention may be practiced without these specific details in one or more aspects. In other instances, well-known protocols, structures and techniques have not been shown in detail in order not to obscure the present invention. Those of ordinary skill in the art will understand that the described techniques and mechanisms can be applied to various architectures that capture the concept drift of data distributions.

[0014] Embodiments of the present invention will be described below with reference to the accompanying drawings. In the following description, numerous specific details are set forth in order to provide a more complete understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced...

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Abstract

The invention provides a method and a system for acquiring concept drift amount of data distribution. The method comprises the steps of obtaining all data including training data and test data; clustering all the data by using a Gaussian mixture model to obtain a plurality of clustering clusters of all the data; respectively obtaining concept drift amounts of data distribution of all data contained in each cluster of the plurality of clusters; and obtaining the concept drift amount of the data distribution of all the data by utilizing the concept drift amount of the data distribution of all the data contained in each cluster of the plurality of clusters. Therefore, the concept drift amount of the data distribution can be accurately obtained, the change condition of the data distribution can be accurately judged, and the reliability of the system is greatly improved.

Description

technical field [0001] The present invention relates to the technical field of machine learning, in particular to a method, a system, a computer system and a computer-readable storage medium for obtaining concept drift of data distribution. Background technique [0002] In recent years, data-driven machine learning has achieved great success in many fields, such as weather prediction, personalized recommendation, product defect detection, etc. However, most data-driven machine learning methods are based on an assumption, either explicitly or implicitly, that the training data and test data belong to the same data distribution. However, in real-world applications, the distribution of data in many fields usually changes over time, and this change may not be foreseen in advance. The change in the data distribution is called concept drift. The emergence of concept drift may cause the prediction results of a model trained and deployed based on historical data in a certain field...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/23G06F18/22G06F18/214
Inventor 刘世霞杨维铠李振
Owner TSINGHUA UNIV
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