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A model training method, device, storage medium and electronic equipment

A technology for model training and predictive models, which is applied in the computer field, can solve the problem of large computational load of predictive models, and achieve the effect of reducing the computational load

Active Publication Date: 2021-09-24
BEIJING SANKUAI ONLINE TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, in the prior art, the amount of input sample data is too large when training the prediction model, which leads to the problem of a large amount of calculation during the training of the prediction model

Method used

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  • A model training method, device, storage medium and electronic equipment
  • A model training method, device, storage medium and electronic equipment
  • A model training method, device, storage medium and electronic equipment

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Embodiment Construction

[0050] In order to make this specification, the technical solutions and advantages will be described in conjunction with the specific embodiments and corresponding drawings of the present specification and the corresponding drawings. Obviously, the described embodiments are merely the embodiments of the present specification, not all of the embodiments. Based on the embodiments in this specification, one of ordinary skill in the art does not have all other embodiments obtained without creative labor, all of which are protected by this specification.

[0051] The technical solutions provided in the present specification are described in detail below with reference to the accompanying drawings.

[0052] figure 1 A model training process provided for the embodiment of the present specification, including:

[0053] S100: The first sample set to be input is acquired; wherein the first sample set comprises at least one sample, and the sample is a historical movement trajectory of the t...

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Abstract

This specification discloses a model training method, device, storage medium, and electronic equipment. According to the embodiment of this specification, according to the predicted trajectory of the target object corresponding to each sample in the first sample set of the input prediction model, the first sample The concentrated samples are screened to obtain training samples. Then, the predictive model is trained based on the training samples. The samples other than the training samples in the first sample set are re-determined as the first sample set, and the above training process is iterated continuously until the training stop condition is satisfied. In this method, when the prediction model is trained, only the selected training samples are used to train the prediction model, instead of using all the samples in the first sample set to train the prediction model, which can reduce the training time of the prediction model. calculation amount.

Description

Technical field [0001] This specification relates to the field of computer technology, in particular, to a model training method, device, storage medium, and electronic device. Background technique [0002] With the development of technology, the machine learning model is widely used in various fields. Taking the automatic driving area as an example, the prediction model is typically used to predict the obstacles around the unmanned equipment to ensure that the unmanned equipment can safely travel. The predictive model can realize the function of trajectory prediction, you need to enter the prediction model to train the predictive model. [0003] In the prior art, it is necessary to obtain a historical movement track data of a large number of obstacles before using the predictive model to predict the trajectory of the obstacles. Then, in the prediction model of all sample data to be trained, the prediction model is trained according to the input sample data to obtain the predicti...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N20/00G01C21/20
CPCG06N20/00G01C21/20G06F18/214
Inventor 樊明宇徐一任冬淳夏华夏朱炎亮钱德恒
Owner BEIJING SANKUAI ONLINE TECH CO LTD