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DTFA Rule Mining-Based Model to Predict Students’ Performance

  • Sushil Kumar VermaEmail author
  • Shailesh Jaloree
  • Ramjeevan Singh Thakur
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 34)

Abstract

Nowadays data mining plays an important role in various fields. This field may be related to education, agriculture or medicine. Education is an important part of human life. With the help of data mining in education called educational data mining, we achieve quality education, which is very essential not only for growth of students as well as country. Based on quality education, we achieve and improve performance of students. We can use the different data mining techniques to improve performance of students. This paper’s contents indicate the sort out the performance of students basis on 12th and graduation level marks, previous semester marks (PSM), mid sem marks (MSM), attendance (ATT) and end semester marks (ESM). Using attributes, conclude the recital of students in end semester. In this paper, for classification, we used decision tree algorithm, and for fuzzy association mining, we used the modified Apriori-like method. In this paper, we will merge these rules which are generated from decision tree algorithm and Apriori-like algorithm.

Keywords

Educational data mining (EDM) Knowledge discovery Decision tree Classification Fuzzy association rule mining 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Sushil Kumar Verma
    • 1
    Email author
  • Shailesh Jaloree
    • 2
  • Ramjeevan Singh Thakur
    • 3
  1. 1.S.A.T.IVidishaIndia
  2. 2.Department of Applied Mathematics and Computer ScienceS.A.T.IVidishaIndia
  3. 3.Department of Computer ApplicationsBhopalIndia

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