Prediction model of middle school student performance based on MBSO and MDBO-BP-Adaboost method.

ABSTRACT: Predictions of student performance are important to the education system as a whole, helping students to know how their learning is changing and adjusting teachers' and school policymakers' plans for their future growth. However, selecting meaningful features from the huge amount of educational data is challenging, so the dimensionality of student achievement features needs to be reduced. Based on this motivation, this paper proposes an improved Binary Snake Optimizer (MBSO) as a wrapped feature selection model, taking the Mat and Por student achievement data in the UCI database as an example, and comparing the MBSO feature selection model with other feature methods, the MBSO is able to select features with strong correlation to the students and the average number of student features selec

SUBMITTER: Fang R 

PROVIDER: S-EPMC11772490 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature