Model training method, device and system

A model training and retraining technology, applied in computing models, character and pattern recognition, instruments, etc., can solve the problem that the model cannot effectively adapt to site analysis equipment, etc., to achieve effective generalization, easy deployment, and reduce training costs Effect

Pending Publication Date: 2021-03-19
HUAWEI TECH CO LTD
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the trained model may not be able to effectively adapt to the needs of site analysis equipment

Method used

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  • Model training method, device and system
  • Model training method, device and system
  • Model training method, device and system

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Embodiment Construction

[0143] In order to make the purpose, technical solution and advantages of the present application clearer, the implementation manners of the present application will be further described in detail below in conjunction with the accompanying drawings.

[0144] In order to facilitate readers' understanding, the embodiment of the present application briefly introduces the machine learning algorithm involved in the provided model training method.

[0145] As an important branch of the AI ​​field, machine learning algorithms have been widely used in many fields. From the perspective of learning methods, machine learning algorithms can be divided into supervised learning algorithms, unsupervised learning algorithms, semi-supervised learning algorithms, and reinforcement learning algorithms. A supervised learning algorithm means that an algorithm can be learned or a model can be established based on training data, and new instances can be speculated based on this algorithm or model. ...

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Abstract

The invention discloses a model training method, device and system, and belongs to the field of AI. The method comprises the following steps: receiving a machine learning model sent by first analysisequipment; and performing incremental training on the machine learning model based on a first training sample set, and feature data in the first training sample set being feature data of a local pointnetwork corresponding to the local point analysis device. The problem that the machine learning model obtained through offline training cannot effectively adapt to the requirements of local point analysis equipment is solved, and the method and the device are used for predicting the classification result.

Description

technical field [0001] The present application relates to the field of artificial intelligence (AI), in particular to a model training method, device and system. Background technique [0002] Machine learning refers to allowing the machine to train a machine learning model based on training samples, so that the machine learning model has the ability to predict the category of samples other than the training samples. [0003] At present, the data analysis system includes multiple analysis devices for data analysis. The multiple analysis devices may include cloud analysis devices and site analysis devices. The deployment method of the machine learning model in the system includes: the cloud analysis device performs model offline training, and then deploy the model after offline training directly on the site analysis device. [0004] However, the trained model may not be able to effectively adapt to the requirements of site analysis equipment. Contents of the invention [0...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N20/00G06K9/62
CPCG06N20/00G06F18/24323G06N5/01G06F18/2433G06N20/20G06F16/9027G06F11/3428
Inventor 薛莉张彦芳张浩张亮李扬
Owner HUAWEI TECH CO LTD
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