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Computer-executed machine learning model training method, device and equipment

A computer and matching model technology, applied in the computer field, can solve the problem of low prediction accuracy of the model

Active Publication Date: 2022-05-17
ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For scenarios where the data is constantly changing over time, the prediction accuracy of the model is usually lower

Method used

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  • Computer-executed machine learning model training method, device and equipment
  • Computer-executed machine learning model training method, device and equipment
  • Computer-executed machine learning model training method, device and equipment

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Embodiment Construction

[0038] The solutions provided in this specification will be described below in conjunction with the accompanying drawings.

[0039] Before describing the scheme provided by this specification, the inventive concept of this scheme is explained as follows.

[0040] In practice, data is constantly changing over time in various scenarios. In the scenario where the data is constantly changing, in order to improve the accuracy of model prediction, it is necessary to adjust the model in real time or in a timely manner based on the changed data. Taking Alipay's smart customer service scenario as an example, with the increasing complexity of Alipay's business and the speed of business changes, users' questions about related business issues are also in a dynamic, rapid and frequent changing trend, which requires smart customer service to be able to Perform frequent update iterations to continuously adapt to new user questions.

[0041] In order to realize real-time or timely adjustmen...

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Abstract

The embodiments of this specification provide a computer-executed machine learning model training method, device, and equipment. In the training method, incremental data within a current time period is acquired as a training sample set. Based on the training sample set, the machine learning model trained in the previous period is incrementally trained to obtain the initial machine learning model. Each test sample in the test sample set is input into the initial machine learning model to obtain test results. Based on the test results, determine the accuracy of the initial machine learning model. If the accuracy rate is greater than the first threshold, the initial machine learning model is used as the machine learning model trained in the current time period. If the accuracy rate is not greater than the first threshold, the test samples with wrong test results in the test sample set are added to the training sample set to obtain an updated training sample set, and based on the updated training sample set, the initial machine learning model is trained. To get the machine learning model trained in the current time period.

Description

technical field [0001] One or more embodiments of this specification relate to the field of computer technology, and in particular to a computer-executed machine learning model training method, device, and equipment. Background technique [0002] With the general popularity of machine learning, various machine learning models are getting more and more attention. For a machine learning model, it is usually necessary to train it based on training data (also called training samples), and then use the trained machine learning model to perform some kind of prediction, such as category prediction. [0003] It should be noted that, in order to ensure the accuracy of the trained machine learning model, it usually needs to be trained based on a large amount of training data, which makes the training process of the model usually more complicated. Because the training process of the model is relatively complicated, in the traditional technology, the training process of the model is us...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N20/00
CPCG06N20/00
Inventor 张望舒温祖杰
Owner ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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