Data mining techniques: Which one is your favorite?

© 2020, © 2020 Taylor & Francis Group, LLC. 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 b...

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Bibliographic Details
Main Authors: Pannapa Changpetch, Moya Reid
Other Authors: Bentley University
Format: Article
Published: 2020
Subjects:
Online Access:https://repository.li.mahidol.ac.th/handle/123456789/57783
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Institution: Mahidol University
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Summary:© 2020, © 2020 Taylor & Francis Group, LLC. 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.