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Data mining techniques: Which one is your favorite?

  • Mahidol University
  • Bentley University

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

Based on a statistical analysis, undergraduate business students are shown to prefer classification tree over six other standard data mining techniques. Data were collected over a 4-year period from students taking a data mining course offered at a business university in the US. The principal reason given by students for this preference is that classification tree is a highly visual technique—a quality that makes its results relatively easy to comprehend. Educators can draw on this information in their classroom practice with both business students and students in other majors taking data mining courses. Researchers can benefit from it in relation to effectively presenting data mining results to multiple audiences.

Original languageEnglish
Pages (from-to)143-148
Number of pages6
JournalJournal of Education for Business
Volume96
Issue number3
DOIs
Publication statusPublished - 2021
Externally publishedYes

Keywords

  • Classification tree
  • Naïve Bayes
  • data mining
  • visual explanation
  • visualization

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