Summary
Data-mining applications often involve quantitative data. However, learning from quantitative data is often less effective and less efficient than learning from qualitative data. Discretization addresses this issue by transforming quantitative data into qualitative data. This chapter presents a comprehensive introduction to discretization. It clarifies the definition of discretization. It provides a taxonomy of discretization methods together with a survey of major discretization methods. It also discusses issues that affect the design and application of discretization methods.
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Yang, Y., Webb, G.I., Wu, X. (2009). Discretization Methods. In: Maimon, O., Rokach, L. (eds) Data Mining and Knowledge Discovery Handbook. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09823-4_6
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DOI: https://doi.org/10.1007/978-0-387-09823-4_6
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