Prediction of Students Performance using Machine learning
J. Dhilipan, N. Vijayalakshmi, S. Suriya, Arockiya Christopher
Abstract
Abstract An enormous measure of computerized information is being produced over a wide assortment in the field of data mining strategies. The creation of student achievement prediction models to predict student performance in academic institutions is a key area of the development of Education Data Mining. A prediction system has been proposed by using their 10th, 12th and previous semester marks. The study is evaluated using Binomial logical regression, Decision tree, and Entropy and KNN classifier. In order to attain their higher score, this framework would assist the student to recognize their final grade and improve their academic conduct.
Topics & Concepts
Decision treeComputer scienceMachine learningArtificial intelligenceEducational data miningDecision tree learningEntropy (arrow of time)Field (mathematics)Academic achievementClassifier (UML)Data miningData scienceMathematics educationMathematicsPhysicsPure mathematicsQuantum mechanicsOnline Learning and AnalyticsArtificial Intelligence in HealthcareIntelligent Tutoring Systems and Adaptive Learning