Prediction of students performance of an institute using ClassificationViaClustering and ClassificationViaRegression

Abstract

Machine Learning is the field of computer science that learns from data by studying algorithms and their constructions. In machine learning, predictions can be made by using certain algorithms for specific inputs. In this paper important classification and clustering algorithms are discussed which can be further applied to BE (Information Technology) Third Semester to evaluate student’s performance. The performance of students of Digital Electronics of University Institute of Engineering and Technology (UIET), Panjab University (PU) is calculated by applying K-Means and Hierarchical Clustering Algorithms. Unsupervised Learning Algorithms like K-Means and Hierarchical clustering are discussed and for supervised learning, M5P algorithm is discussed. Further a comparison between ClassificationViaClustering and ClassificationViaRegression is done using WEKA Tool. The accuracy of grades prediction is calculated with both the approaches and a graphical explanation is presented for the BE (Information Technology) Third Semester students.