In order to realize the reliability evaluation of college students’ mental health quality, a model of college students’ mental health quality evaluation based on computational intelligence is proposed. The mutual information quantity is used as the benchmark parameter to measure the interaction between the two variables of college students’ mental health quality. The greedy algorithm to find the best feature subset for college students’ mental health quality assessment is designed. The feature sequence sampling and the reassembly model of college students’ mental health quality is constructed. The reliability assessment and nonparametric quantitative feature estimation are carried out, so as to complete the quantitative analysis and assessment of college students’ mental health quality. The test results show that this method has a high confidence level and good reliability. The evaluation results can accurately reflect the depression, stress, anxiety, and other emotions related to college students’ mental health, and have a good effect.
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