Inferiority complex of higher vocational students based on improved random sampling

JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING(2021)

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Abstract
Some factors affecting the physical and mental health of vocational college students, the sense of inferiority plays a very important role in cultivating students with physical and mental health. Inverse random under sampling algorithm is improved based on integrated learning, which can improve the performance of the classifier. Stacking integrated learning and flip random sampling reduction algorithm SIRUS is proposed. Select the individual subjective factors studied in this paper is important in self-attribution and social objective factors are important social support factors, and the only demographic variables is a significant difference.
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Key words
Vocational students, inferiority feeling, attribution, social support, sampling algorithm, random sampling
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