Model training method and device, poverty degree information identification method and device and storage medium
A model training and model technology, applied in the computer field, can solve the problems of strong subjectivity, inaccurate identification results of poor individuals, low identification efficiency of poor individuals, etc., and achieve the effect of strong classification performance
Active Publication Date: 2021-03-23
北京北明数科信息技术有限公司
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Problems solved by technology
In the existing technology, the information of each individual is checked by manual investigation, and whether the individual is determined to be a poor individual is determined by subjective criteria. Therefore, the identification efficiency of the poor individual in the existing technology is low, and due to strong subjectivity, it is easily interfered by cheating factors , resulting in inaccurate identification of poor individuals
Method used
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Embodiment Construction
[0043] In this embodiment, the artificial intelligence model that has been trained and tested is used to identify the poverty degree information. Before using the artificial intelligence model, train the artificial intelligence model. refer to figure 1 , training the artificial intelligence model mainly includes the following steps:
[0044] P1. Obtain multiple neural networks; each neural network has a sequence relationship;
[0045] P2. Obtain multiple feature data and the tag values corresponding to the feature data; the feature data is extracted from the student data, and the tag value includes information used to describe the corresponding poverty level of the students;
[0046] P3. Determine the weight set; the elements of the weight set are the weights corresponding to each feature data;
[0047] P4. Execute multiple rounds of training and testing process until the termination condition is met; in a round of training and testing process, the feature data and weight...
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The invention discloses an artificial intelligence model training method, a poverty degree information identification method, a computer device and a storage medium, and the artificial intelligence model training method comprises the steps of obtaining a plurality of neural networks, feature data and label values, and executing a plurality of rounds of training and testing processes until a termination condition is met; and determining a sample weight set and corresponding weights of the neural networks, and recombining the neural networks into an artificial intelligence model according to thecorresponding weights. The invention has the capability of identifying the poverty degree information to which the student data belong, and the weight set of the feature data used for training the neural network in the next order is adjusted according to the training result of the neural network in the previous order, so that the training result of the neural network in the previous order can betransmitted to the training process of the neural network in the later order, and the finally obtained artificial intelligence model has strong classification performance. The invention is widely applied to the technical field of computers.
Description
technical field [0001] The invention relates to the field of computer technology, in particular to an artificial intelligence model training method, a poverty level information identification method, a computer device and a storage medium. Background technique [0002] In the fields of social poverty alleviation and campus poverty alleviation, there is a need to identify individuals who meet the poverty standard from the crowd. In the existing technology, the information of each individual is checked by manual investigation, and whether the individual is determined to be a poor individual is determined by subjective criteria. Therefore, the identification efficiency of the poor individual in the existing technology is low, and due to strong subjectivity, it is easily interfered by cheating factors , resulting in inaccurate identification of poor individuals. Contents of the invention [0003] Aiming at at least one of the above technical problems, the purpose of the prese...
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IPC IPC(8): G06N3/04G06N3/08G06Q50/20G06Q50/26
CPCG06N3/08G06Q50/205G06Q50/26G06N3/047G06N3/045
Inventor 奚宇航蔡庆秋
Owner 北京北明数科信息技术有限公司