Regression model construction optimization method and device, medium and computer program product

An optimization method and regression model technology, applied in the regression model construction optimization method, medium and computer program products, equipment fields, can solve the problem of low regression model construction efficiency and so on

Pending Publication Date: 2021-07-09
WEBANK (CHINA)
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Problems solved by technology

[0004] The main purpose of this application is to provide a regression model construction optimization method, equipment, media and computer program pr

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  • Regression model construction optimization method and device, medium and computer program product
  • Regression model construction optimization method and device, medium and computer program product
  • Regression model construction optimization method and device, medium and computer program product

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Embodiment Construction

[0034] It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application.

[0035] The embodiment of the present application provides a regression model construction and optimization method. In the first embodiment of the regression model construction and optimization method of the present application, refer to figure 1 , the regression model construction optimization method includes:

[0036] Step S10, obtaining feature data from each preset data source, and generating prediction weight parameters corresponding to each of the feature data based on each preset regression parameter prediction model and the data source missing probability of each of the preset data sources ;

[0037] In this embodiment, it should be noted that the regression model construction optimization method is used to construct a linear regression model, and the preset regression parameter prediction model is a neura...

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Abstract

The invention discloses a regression model construction optimization method and device, a medium and a computer program product, and the method comprises the steps: obtaining feature data from each preset data source, and predicting the feature data of each preset data source based on each preset regression parameter prediction model and the data source missing probability of each preset data source, respectively generating prediction weight parameters corresponding to the feature data; generating a prediction regression value based on each prediction weight parameter and each feature data; and constructing a target regression model by optimizing each preset regression parameter prediction model based on the real regression value and the prediction regression value corresponding to each feature data. The technical problem of low regression model construction efficiency caused by data source missing is solved.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence in financial technology (Fintech), and in particular to a regression model construction optimization method, equipment, media and computer program products. Background technique [0002] With the continuous development of financial technology, especially Internet technology finance, more and more technologies (such as distributed, artificial intelligence, etc.) The industry also has higher requirements for the distribution of to-do items. [0003] With the continuous development of computer technology, the application of artificial intelligence is becoming more and more extensive. At present, in real scenarios, it is often necessary to use data from multiple data sources to construct regression models, where each data source provides different data for the regression model. In the process of building a regression model, some data sources are often missing suddenly, that ...

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Application Information

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IPC IPC(8): G06N20/00G06N3/08
CPCG06N3/08G06N20/00
Inventor 康焱刘洋梁新乐
Owner WEBANK (CHINA)
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