Bibliographic Details
| Title: |
Application of Improved SMOTE and XGBoost Algorithm in the Analysis of Psychological Stress Test for College Students. |
| Authors: |
Du, Wei1 (AUTHOR) |
| Source: |
Journal of Electrical & Computer Engineering. 5/19/2022, p1-8. 8p. |
| Subject Terms: |
*PSYCHOLOGICAL stress testing, *COLLEGE students, *PSYCHOLOGICAL stress, *ALGORITHMS, *SAMPLING (Process) |
| Abstract: |
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. [ABSTRACT FROM AUTHOR] |
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