Accurate prediction of college students' information anxiety based on optimized random forest and category boosting fusion model
Abstract The paper aims to construct an efficient predictive model to accurately predict information anxiety among college students and provides a scientific basis for mental health interventions. Firstly, the random forest algorithm is used to preprocess the relevant data and select the best featur...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-05-01
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| Series: | Discover Artificial Intelligence |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44163-025-00328-3 |
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