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Academic early warning method based on lifting tree model

A tree model and academic technology, applied in the field of academic early warning based on the lifting tree model, can solve the problems of lack of timeliness and late time nodes, and achieve the effects of high prediction efficiency, high timeliness and high efficiency

Pending Publication Date: 2020-06-09
NORTHWEST UNIV(CN)
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Problems solved by technology

[0008] Therefore, the traditional early warning method for students’ academic performance is mainly aimed at students whose academic credits and accumulated academic credits have reached the threshold in the previous semester. The students are given early warnings. The accuracy is achieved, but the time node is too late and lacks timeliness.

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  • Academic early warning method based on lifting tree model
  • Academic early warning method based on lifting tree model
  • Academic early warning method based on lifting tree model

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Embodiment Construction

[0053] The present invention is further described below in conjunction with the embodiments and accompanying drawings, but the present invention is not limited to the following embodiments.

[0054] Such as figure 1 , 2 As shown, in the embodiment of the present invention, an academic early warning method based on the lifting tree model is proposed. The data used in the present invention can clearly outline the student's space-time campus trajectory map with the individual student as the unit, and obtain more accurately For the student feature data, the boosted tree model based on the AdaBoost algorithm is adopted, and the weak classifier of the decision tree is combined with the AdaBoost algorithm to upgrade to a strong classifier, thereby achieving a higher precision and recall rate.

[0055] The basic process of this program is:

[0056] An academic early warning method based on the promotion tree model, which includes collecting the student's mobile device terminal netwo...

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Abstract

The invention discloses an academic early warning method based on a lifting tree model. The method comprises the steps of firstly, obtaining a student school mobile device terminal networking data setand a student score data set, taking a student individual as a unit, determining the identity of the student individual through a student mobile device terminal MAC address and an internet account, drawing the space-time campus behavior track of a student according to time, place and duration of Wi-Fi connection in a school, and then preprocessing student networking data and score data to obtain a standard data set; taking a month as a period, training the boosting tree model by using the training set data, inputting the to-be-predicted data into the model to obtain student data needing early warning, and sending the student data to related personnel. The school space-time behavior track of the student is obtained by analyzing the internet surfing data of the student in-school mobile device terminal connection network, data mining is applied to early warning of student academic affairs, and an academic early warning method is provided for researchers.

Description

technical field [0001] The invention belongs to the technical field of computer data mining, and in particular relates to a learning early warning method based on a lifting tree model. Background technique [0002] At present, with the development of higher education in my country, the analysis of survey data shows that the probability of high school students passing the college entrance examination in 2019 and going to college has reached 100%, and the number of ordinary colleges and universities has reached more than 2,500. However, due to the poor education management of some colleges and universities, students frequently fail courses, delay graduation or even fail to obtain degree certificates, resulting in poor employment conditions for school graduates. Therefore, how to improve the quality of training students and how to improve the competitiveness of students in employment and further education has become an important problem that colleges and universities need to so...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/20G06K9/62
CPCG06Q10/06393G06Q50/205G06F18/214
Inventor 杨建锋陈彦超凌瑜暄朱海阳刘瑞献熊剑民魏瀚哲
Owner NORTHWEST UNIV(CN)
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