Abstract
We present a human-centered approach to model selection in machine learning and data mining that emphasizes and facilitates the active participation of the user in the knowledge discovery process with quantitative and qualitative evaluation of patterns/models. The key idea of such a model selection is it would result from a combination of a quantitative evaluation of model characteristics and performance metrics with a qualitative evaluation of patterns/model by the user. We develop data mining methods integrated with visualization tools in the user-centered visual system D2MS (Data Mining with Model Selection). We finally present a case-study of D2MS in mining stomach cancer data.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-0-387-35602-0_35
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© 2002 IFIP International Federation for Information Processing
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Ho, T.B., Nguyen, T.D., Nguyen, D.D. (2002). A User-Centered Visual Approach to Data Mining. In: Musen, M.A., Neumann, B., Studer, R. (eds) Intelligent Information Processing. IIP 2002. IFIP — The International Federation for Information Processing, vol 93. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35602-0_19
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DOI: https://doi.org/10.1007/978-0-387-35602-0_19
Publisher Name: Springer, Boston, MA
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