Instructor Performance Evaluation Through Machine Learning Algorithms

Abstract

Development in the data mining approaches promotes the researches over the classification of features in the provided dataset. The applications like student performance evaluation plays important role in measuring efficiency of the instructors in the educational institution. Student evaluation feedback database, analyze the performance of the instructors based on the course Id, attendance, difficulty and repetition of selection course by the student. The student evaluation dataset collect from UCI machine learning repository. The accuracy of the feedback provided by the student’s measure with deep learning algorithm. Several Instances record to improve the efficiency of the performance evaluation system. The implementation of neural network along with linear regression model, multiple regression model, feed forward network and Association rules apply for student evaluation database. The performance plots were used to compare the efficiency of the deep learning algorithm over the applied data set.