Student Performance and Prediction System

Predicting the student performance is an important task for the students in colleges the factors which affects the student overall performance are quizzes, lab exams, mid, and final exams. The student exam performance should be informed to their teachers in advance that will decrease the student’s failure chances and increase the performance by focusing on such topics in this students are weak. In this paper machine learning multiple linear regression algorithms is implemented to predict the student’s academic performance the performance of an algorithm has been evaluated based on confusion matrix, accuracy, precision, recall, and F1 score. The Student performance prediction is a crucial job because the large or big volume of data in educational databases. This work is being addressed by educational data mining. EDM developed methods for discovering data that is derived from educational environment. These methods are used for understand student and their learning environment and their interests also. The educational institutions are curious that how many students will be pass and fail for necessary arrangements.