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Student’s Performance Evaluation of an Institute Using Various Classification Algorithms

Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 10)

Abstract

Machine learning is the field of computer science that learns from data by studying algorithms and their constructions. The student’s performance based on slow learner method plays a significant role in nourishing the skills of a student with slow learning ability. The performance of the students of Digital Electronics of University Institute of Engineering and Technology (UIET), Panjab University (PU), Chandigarh is calculated by applying two important classification algorithms (Supervised Learning): Multilayer Perceptron and Naïve Bayes. Further, a comparison between these classification algorithms is done using WEKA Tool. The accuracy of grades prediction is calculated with these classification algorithms and a graphical explanation is presented for the BE (Information Technology) third semester students.

Keywords

Classification WEKA Naïve Bayes Multilayer perceptron 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of ITUIET, Panjab UniversityChandigarhIndia

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