Research On The Application Of Math Grade Prediction System Based On Logistic Regression

In recent years,as China's overall national strength continues to increase,our country's education has also achieved considerable development.Mathematics education is still a very important part of the education system in China.It is the main body of basic education in our country,and it is an indispensable part of the development of diversified education in China.This article focuses on the field of education and conducts research in the following areas:Analyze and study Educational Data Mining(EDM),and design and implement the mathematical mathematics prediction as a sub-module of educational data mining.Before the study,first explain the basic technical knowledge used in the model and system,such as the definition of data mining and theoretical knowledge,EDM research characteristics and EDM domestic and international research status,machine learning definitions,Logistic Regression,Xgboost algorithm,Random Forest Algorithm,Rasch Model algorithm.This article will give a more detailed description of the data preprocessing process.After obtaining high-quality data,the original attributes of the data are analyzed,and in combination with relevant knowledge in the professional field,highquality features are designed to be generated.These characteristics will have a direct impact on the model prediction effect.Therefore,the data preprocessing and feature construction work will occupy 90% of all the time of the system.Next,use the Logistic Regression,Xgboost,and Random Forest algorithms to model the data and adjust the parameters.Then combine these three models to generate a highly accurate prediction model.It is concluded that the use of student history answer data can predict the feasibility of students' answer results and the feasibility of their prediction accuracy is extremely high.From a scientific point of view,the ability to predict errors with unknown data proves that students and teachers can find out the basic factors for students' difficulty in answering questions.Understanding these factors can be of great help in designing high quality courses and lesson plans.