Model training method and related equipment

Abstract

The embodiment of the invention provides a model training method and related equipment, which are used for improving the accuracy of a model and reducing the model training time. The method comprisesthe steps that N prediction topics are determined, and N is a positive integer larger than or equal to 1; factor labeling is carried out on the data corresponding to the N prediction themes to obtainN groups of labeling factors, and the N prediction themes correspond to the N groups of labeling factors; the N groups of labeling factors are preprocessed to obtain the N key data sets; the single factor analysis is performed on each key data set in the N key data sets to obtain N groups of target factors, the N groups of target factors having an association relationship with the N prediction themes; and training the N groups of target factors through at least one model algorithm to obtain at least one model corresponding to the N prediction topics.

Description

technical field [0001] The present application relates to the field of model training, in particular to a model training method and related equipment. Background technique [0002] With the advancement of the Internet, researchers from all walks of life have gradually realized the importance of data applications and began to tap the potential massive application value of data. Powerful data mining tools can improve the credibility of data results, reduce the difficulty of researchers, and improve research efficiency. R is not only a programming language, but also a software that integrates various algorithms and functions. It is open source, free and non-commercial. This software integrates a large number of commonly used data mining and analysis algorithms, including classification algorithms and regression algorithms. , neural network, etc., users can adjust the algorithm parameters according to their needs, and it also includes visual analysis functions, which can meet m...

AI Technical Summary

Problems solved by technology

[0004] The existing data has defects such as long acquisition period, limited variables, and many interference factors. Traditional research generally uses statistical methods, most of which are to study the impact of a single factor on the research purpose, and seldom explain the relationship between multiple factors.

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