Using MDS preference plot as visual analytics of data: A machine learning approach
The primary purpose of this paper is to advocate the use of multidimensional scaling (MDS) preference plot to study relationships among variables and individual differences in these variables. MDS preference plot is not a new visual technique; nevertheless, its application to visualize individual di...
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| Published in: | Methodological innovations Vol. 16; no. 1; pp. 67 - 77 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
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London, England
SAGE Publications
01.03.2023
Sage Publications Ltd SAGE Publishing |
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| ISSN: | 2059-7991, 2059-7991 |
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| Abstract | The primary purpose of this paper is to advocate the use of multidimensional scaling (MDS) preference plot to study relationships among variables and individual differences in these variables. MDS preference plot is not a new visual technique; nevertheless, its application to visualize individual differences in variables for high-dimensional data is rare, particularly in education and social sciences. We illustrated its application using a real example in an educational setting. The results indicate that the MDS preference plot is a viable visualization technique for data mining and analytics. Traditional statistical methods, such as the analysis of variance, can be used to further support the visual analysis results. |
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| AbstractList | The primary purpose of this paper is to advocate the use of multidimensional scaling (MDS) preference plot to study relationships among variables and individual differences in these variables. MDS preference plot is not a new visual technique; nevertheless, its application to visualize individual differences in variables for high-dimensional data is rare, particularly in education and social sciences. We illustrated its application using a real example in an educational setting. The results indicate that the MDS preference plot is a viable visualization technique for data mining and analytics. Traditional statistical methods, such as the analysis of variance, can be used to further support the visual analysis results. |
| Author | Ding, Cody Zhang, Yan |
| Author_xml | – sequence: 1 givenname: Yan surname: Zhang fullname: Zhang, Yan – sequence: 2 givenname: Cody orcidid: 0000-0002-2894-1545 surname: Ding fullname: Ding, Cody email: dingc@umsl.edu |
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| Cites_doi | 10.1016/j.compedu.2020.103855 10.1007/s10763-007-9090-y 10.1007/s40593-016-0110-3 10.1145/1743546.1743567 10.1037/amp0000886 10.1177/016146811812001302 10.1177/00131610021969092 10.1037/a0037802 10.1016/j.compedu.2018.03.018 10.3389/fpsyg.2017.01666 10.1377/hlthaff.2015.0642 10.1177/1745691620917333 10.1002/9780470973196 10.1007/978-3-540-70956-5_1 10.18608/jla.2015.23.3 10.4135/9781446201015 10.1787/9789264281820-en 10.1198/106186008X318440 10.1023/A:1013176309260 10.5465/amj.2018.4005 10.1093/biomet/58.3.453 10.1016/j.caeai.2020.100001 10.1177/1745691616663875 10.1186/s41239-020-0177-7 10.1016/S0272-7757(97)00040-X 10.3389/feduc.2020.00104 10.1016/j.paid.2012.01.018 10.3102/0162373715576077 |
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| Keywords | visual analytics MDS preference plot data mining Machine learning biplot |
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| SubjectTerms | Cognitive style Data mining Education Individual differences Information retrieval Machine learning Measures Social sciences Statistical methods Variables Variance analysis Visualization |
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| Title | Using MDS preference plot as visual analytics of data: A machine learning approach |
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