Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance

Table 7

Accuracy results for Naive Bayes.

Study	Year	Predictive features	Accuracy (%)
[42]	2015	Attendance, internal grade, computer skills, school level, mobile, tuition, type of school, type of board, and gender	65.1
[3]	2016	Age, section, program, method, place of birth, transport, subject, motivation level, homework, tuition, parent education, attendance, communication, GPA, quiz, assignment, lab test, and final exam	86
[60]	2017	List of subjects and grades	83.6
[19]	2018	Gender, age, admission, attendance, study mode, program, education status, book resources, and quiz	72.4
[15]	2018	CGPA, high risk, coursework, examination, plagiarism count, campus access, and off-campus access	90
[49]	2015	Number of views/post of student, course information, student information, submitted assignments, and progress of assignments	96.9