Linear Regression Model in Student Prediction System

Linear Regression Model in Student Prediction System

IDr. B. Azhagusundari, II Dr John Grasias S, III G Sudha, IV G.Kanimozhi, V Dr. Radhika.V

1.   Dr.B.Azhagusundari ,Associate Professor, Department of Computer Science NGM College

    Pollachi,azhagusundari@ngmc.org

2.  Dr John Grasias S,Assistant Professor,Department of Computer Science ,AJK College of Arts

     and Science ,Coimbatore, johngrasias@gmail.com

3. G Sudha, Computer Instructor, Govt Girls Hrs Sec School Ekanampet Kanchipuram 631601

     sudhasganapathi@gmail.com

4. G.Kanimozhi, Assistant Professor, Department of Computer Science, National College

    (Autonomous), Trichy, gajekani@gmail.com

5. Dr. Radhika.V, Department of Physics, Erode Sengunthar Engineering College College

   (AUTONOMOUS), Thudupathy, Perundurai – 638057,Tamil Nadu,radhikaesec@gmail.com

Abstract

Logistic Regression is a widely used statistical method for predicting a categorical dependent variable based on a set of independent variables. Recognized for its adaptability and frequent application, logistic regression is particularly effective in modeling binary and multinomial outcomes. This paper provides a clear and detailed exploration of the fundamental concepts of logistic regression and demonstrates its application in predictive analysis using student data. Through this practical example, the paper highlights the method's utility in identifying relationships and making informed predictions in student educational contexts.

Keywords: categorical variable, logistic regression, Prediction system, student data