Classification Through Discriminant Analysis Over Educational Dataset

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 701)

Abstract

This work highlights the effective strategy for classification values related to categorical dependent using discriminant function analysis. A personal dataset of students was created with social, economical, and academic variables for the actual empirical analysis. The discriminant function analysis was implemented to study the behavior patterns against the performance of students. It was observed that some of the variables are playing an important role in discrimination and based on our data, as we found 67.4% is the only correct classification.

Keywords

Discriminant function analysis Data mining Analysis of patterns Statistical analysis 

Notes

Declaration

Authors hereby declare that the student data has been collected from college with informed consent from the college management as well as higher authorities.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Parag Bhalchandra
    • 1
  • Aniket Muley
    • 2
  • Mahesh Joshi
    • 3
  • Santosh Khamitkar
    • 1
  • Hanumant Fadewar
    • 1
  • Pawan Wasnik
    • 1
  1. 1.School of Computational SciencesS.R.T.M. UniversityNandedIndia
  2. 2.School of Mathematical SciencesS.R.T.M. UniversityNandedIndia
  3. 3.School of Educational SciencesS.R.T.M. UniversityNandedIndia

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