Search

Analyzing the evaluation data of students to teachers in the teaching evaluation system helps teachers understand the true attitudes of students to teachers, summarize teaching experience, improve subsequent teaching methods, and improve teaching quality. However, when evaluating teaching, random or malicious evaluations may occur among students, resulting in a large amount of noise in the evaluation data, which results in unsatisfactory feedback data. Therefore, this paper proposes a discrete Poisson mixture model to model the evaluation data of students with noise. Each discrete Poisson component in the mixture model corresponds to a class of students with similar evaluation modes. The model parameters in the loose distribution represent the evaluation scores in the corresponding evaluation mode. The log-likelihood function is constructed to measure the degree of fit between the mixed model and the evaluation data, and the gradient descent method is used to solve the model parameters with the highest degree of fit, to find the true evaluation of the students to the teacher, and to ensure the teacher student relationship in the teaching evaluation system Communicate effectively. A large number of experimental results show that the model in this paper can quickly and accurately identify students with different evaluation modes from the evaluation data containing noise, and grasp the true evaluation of the students to teachers. [ABSTRACT FROM AUTHOR]