Application of Improved SMOTE and XGBoost Algorithm in the Analysis of Psychological Stress Test for College Students

To address the phenomenon of serious psychological stress among college students, there are problems of high cost and subjectivity in assessing psychological stress by collecting physiological data, and this paper proposes a stress assessment method (Improved SMOTE + XGBoost) based on intelligent da...

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Main Author: Wei Du
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Electrical and Computer Engineering
Online Access:http://dx.doi.org/10.1155/2022/2760986
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author Wei Du
author_facet Wei Du
author_sort Wei Du
collection DOAJ
description To address the phenomenon of serious psychological stress among college students, there are problems of high cost and subjectivity in assessing psychological stress by collecting physiological data, and this paper proposes a stress assessment method (Improved SMOTE + XGBoost) based on intelligent data collection, which divides stress levels into five levels. In the process of processing a large amount of data, there will be too little data. Therefore, this paper applies the improved SMOTE method to the data preprocessing, which can reduce the difficulty of collecting psychological stress test data while ensuring the amount of data. Firstly, we extracted features from cell phone data to generate samples, processed the samples by SMOTE, and then filtered features by XGBoost algorithm to filter features; meanwhile, we trained RF, SVM, BP, and KNN with the data before and after sampling and before and after feature screening, and the results showed that Improved SMOTE + XGBoost outperformed other methods.
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spelling doaj-art-ebed5798f8fd46d6bbbb2cce472afe202025-02-03T05:53:34ZengWileyJournal of Electrical and Computer Engineering2090-01552022-01-01202210.1155/2022/2760986Application of Improved SMOTE and XGBoost Algorithm in the Analysis of Psychological Stress Test for College StudentsWei Du0Psychological Health Education and Counseling CenterTo address the phenomenon of serious psychological stress among college students, there are problems of high cost and subjectivity in assessing psychological stress by collecting physiological data, and this paper proposes a stress assessment method (Improved SMOTE + XGBoost) based on intelligent data collection, which divides stress levels into five levels. In the process of processing a large amount of data, there will be too little data. Therefore, this paper applies the improved SMOTE method to the data preprocessing, which can reduce the difficulty of collecting psychological stress test data while ensuring the amount of data. Firstly, we extracted features from cell phone data to generate samples, processed the samples by SMOTE, and then filtered features by XGBoost algorithm to filter features; meanwhile, we trained RF, SVM, BP, and KNN with the data before and after sampling and before and after feature screening, and the results showed that Improved SMOTE + XGBoost outperformed other methods.http://dx.doi.org/10.1155/2022/2760986
spellingShingle Wei Du
Application of Improved SMOTE and XGBoost Algorithm in the Analysis of Psychological Stress Test for College Students
Journal of Electrical and Computer Engineering
title Application of Improved SMOTE and XGBoost Algorithm in the Analysis of Psychological Stress Test for College Students
title_full Application of Improved SMOTE and XGBoost Algorithm in the Analysis of Psychological Stress Test for College Students
title_fullStr Application of Improved SMOTE and XGBoost Algorithm in the Analysis of Psychological Stress Test for College Students
title_full_unstemmed Application of Improved SMOTE and XGBoost Algorithm in the Analysis of Psychological Stress Test for College Students
title_short Application of Improved SMOTE and XGBoost Algorithm in the Analysis of Psychological Stress Test for College Students
title_sort application of improved smote and xgboost algorithm in the analysis of psychological stress test for college students
url http://dx.doi.org/10.1155/2022/2760986
work_keys_str_mv AT weidu applicationofimprovedsmoteandxgboostalgorithmintheanalysisofpsychologicalstresstestforcollegestudents