Machine learning model construction method and device, storage medium and program product

By receiving user input modeling requirements and training data sets, using pre-trained language models to generate detailed modeling configuration information, and automatically controlling automated machine learning tools to perform model construction tasks, solving the problems of cumbersome construction process and high professional knowledge requirements in traditional machine learning models, and achieving an efficient and automated model construction process.

CN120218285APending Publication Date: 2025-06-27ANT BLOCKCHAIN TECHNOLOGY (SHANGHAI) CO LTD
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Patent Information

Application Number
CN202510374713.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-26
Publication Date
2025-06-27

AI Technical Summary

Technical Problem

The construction process of traditional machine learning models is cumbersome, time-consuming, and requires high professional knowledge of operators, which limits non-professional personnel to quickly and efficiently complete model construction.

Method used

By receiving the modeling requirements and training data sets input by users, modeling configuration prompts are generated, and detailed modeling configuration information is generated using pre-trained language models, and automated machine learning tools are automatically controlled to perform machine learning model construction tasks, realizing the full process automation from data processing to model training.

Benefits of technology

It lowers the professional threshold and significantly improves modeling efficiency, allowing users to obtain high-quality machine learning models without deep understanding of machine learning theory, reducing the errors that may be caused by manual settings.

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Abstract

One or more embodiments of the invention provide a machine learning model construction method and device, a storage medium and a program product. The method comprises the following steps: receiving a modeling demand input by a user and a training data set for generating a training sample, wherein the modeling demand is at least used for describing a task and a performance requirement of a to-be-constructed machine learning model; generating a modeling configuration prompt based on the modeling demand and the training data set, and inputting the modeling configuration prompt into a pre-training language model, so as to generate modeling configuration information used for describing the configuration content of each link in the automatic modeling process by using the pre-training language model; based on the training data set and the modeling configuration information, the automatic machine learning tool is controlled to execute a machine learning model construction task, and the machine learning model construction task comprises the steps of constructing a to-be-trained machine learning model and a training sample, and training the to-be-trained machine learning model by using the training sample, and obtaining a trained machine learning model.
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