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Forward model selection method and device and readable storage medium

A model selection and training model technology, applied in design optimization/simulation, etc., can solve problems such as low efficiency and high modeling threshold

Pending Publication Date: 2020-06-05
WEBANK (CHINA)
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The main purpose of this application is to provide a forward model selection method, device and readable storage medium, aiming to solve the technical problems of high modeling threshold and low efficiency of forward selection mode in the prior art

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  • Forward model selection method and device and readable storage medium
  • Forward model selection method and device and readable storage medium
  • Forward model selection method and device and readable storage medium

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Embodiment Construction

[0082] It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0083] An embodiment of the present application provides a forward model selection method, which is applied to a forward model selection device. In the first embodiment of the forward model selection method of the present application, refer to figure 1 , the forward model selection method includes:

[0084] Step S10, receiving configuration parameters sent by a client associated with the server, and training a preset initial model based on the configuration parameters to obtain a model to be trained;

[0085] In this embodiment, it should be noted that the client includes a visual interface, on which the user can configure the parameters of the preset model to be trained for model training, such as figure 2 Shown is a visual interface for configuring the parameters, wherein the parameters such a...

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Abstract

The invention discloses a forward model selection method and device and a readable storage medium. The forward model selection method comprises the following steps: receiving configuration parameterssent by a client associated with the server, training a preset initial model based on the configuration parameters; obtaining a model to be trained, obtaining features to be trained, calculating a first significance of each to-be-trained feature; based on each first saliency, selecting a target feature meeting a preset significance requirement from the features to be trained, to carry out loop training on the to-be-trained model based on the target features to obtain a loop training model set, selecting a target training model in the loop training model set based on the configuration parameters, generating visual data corresponding to the target training model, and feeding back the visual data to the client. The technical problems of high forward selection mode modeling threshold and low efficiency are 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 forward model selection method, device and readable storage medium. Background technique [0002] With the continuous development of financial technology, especially Internet technology and finance, more and more technologies (such as distributed, blockchain, artificial intelligence, etc.) Requirements, such as the distribution of corresponding to-do items in the financial industry also have higher requirements. [0003] With the continuous development of computer software and artificial intelligence, the application of machine learning modeling is becoming more and more extensive. In existing technologies, scenarios such as financial risk control and medical models are usually modeled using logistic regression models. In model modeling, the forward selection mode is an important model selection strategy. Compared...

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Application Information

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IPC IPC(8): G06F30/27
CPCG06F30/27
Inventor 唐兴兴黄启军陈瑞钦林冰垠李诗琦
Owner WEBANK (CHINA)